From 98aaa3810be6eb0b83613e86c32fc6f8f55a9b9c Mon Sep 17 00:00:00 2001
From: qingen <qingenz123@126.com>
Date: Wed, 12 Jan 2022 20:07:56 +0800
Subject: [PATCH 1/9] add DER scripts to calculate Diarization Error Rate

---
 utils/DER.py | 152 +++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 152 insertions(+)
 create mode 100755 utils/DER.py

diff --git a/utils/DER.py b/utils/DER.py
new file mode 100755
index 000000000..4c67c4c7b
--- /dev/null
+++ b/utils/DER.py
@@ -0,0 +1,152 @@
+"""Calculates Diarization Error Rate (DER) which is the sum of Missed Speaker (MS),
+False Alarm (FA), and Speaker Error Rate (SER) using md-eval-22.pl from NIST RT Evaluation.
+
+Authors
+ * Neville Ryant 2018
+ * Nauman Dawalatabad 2020
+
+Credits
+ This code is adapted from https://github.com/nryant/dscore
+"""
+
+import os
+import re
+import subprocess
+import numpy as np
+
+FILE_IDS = re.compile(r"(?<=Speaker Diarization for).+(?=\*\*\*)")
+SCORED_SPEAKER_TIME = re.compile(r"(?<=SCORED SPEAKER TIME =)[\d.]+")
+MISS_SPEAKER_TIME = re.compile(r"(?<=MISSED SPEAKER TIME =)[\d.]+")
+FA_SPEAKER_TIME = re.compile(r"(?<=FALARM SPEAKER TIME =)[\d.]+")
+ERROR_SPEAKER_TIME = re.compile(r"(?<=SPEAKER ERROR TIME =)[\d.]+")
+
+
+def rectify(arr):
+    """Corrects corner cases and converts scores into percentage.
+    """
+
+    # Numerator and denominator both 0.
+    arr[np.isnan(arr)] = 0
+
+    # Numerator > 0, but denominator = 0.
+    arr[np.isinf(arr)] = 1
+    arr *= 100.0
+
+    return arr
+
+
+def DER(
+    ref_rttm,
+    sys_rttm,
+    ignore_overlap=False,
+    collar=0.25,
+    individual_file_scores=False,
+):
+    """Computes Missed Speaker percentage (MS), False Alarm (FA),
+    Speaker Error Rate (SER), and Diarization Error Rate (DER).
+
+    Arguments
+    ---------
+    ref_rttm : str
+        The path of reference/groundtruth RTTM file.
+    sys_rttm : str
+        The path of the system generated RTTM file.
+    individual_file : bool
+        If True, returns scores for each file in order.
+    collar : float
+        Forgiveness collar.
+    ignore_overlap : bool
+        If True, ignores overlapping speech during evaluation.
+
+    Returns
+    -------
+    MS : float array
+        Missed Speech.
+    FA : float array
+        False Alarms.
+    SER : float array
+        Speaker Error Rates.
+    DER : float array
+        Diarization Error Rates.
+
+    Example
+    -------
+    >>> import pytest
+    >>> pytest.skip('Skipping because of Perl dependency')
+    >>> ref_rttm = "../../samples/rttm_samples/ref_rttm/ES2014c.rttm"
+    >>> sys_rttm = "../../samples/rttm_samples/sys_rttm/ES2014c.rttm"
+    >>> ignore_overlap = True
+    >>> collar = 0.25
+    >>> individual_file_scores = True
+    >>> Scores = DER(ref_rttm, sys_rttm, ignore_overlap, collar, individual_file_scores)
+    >>> print (Scores)
+    (array([0., 0.]), array([0., 0.]), array([7.16923618, 7.16923618]), array([7.16923618, 7.16923618]))
+    """
+
+    curr = os.path.abspath(os.path.dirname(__file__))
+    mdEval = os.path.join(curr, "../../tools/der_eval/md-eval.pl")
+
+    cmd = [
+        mdEval,
+        "-af",
+        "-r",
+        ref_rttm,
+        "-s",
+        sys_rttm,
+        "-c",
+        str(collar),
+    ]
+    if ignore_overlap:
+        cmd.append("-1")
+
+    try:
+        stdout = subprocess.check_output(cmd, stderr=subprocess.STDOUT)
+
+    except subprocess.CalledProcessError as ex:
+        stdout = ex.output
+
+    else:
+        stdout = stdout.decode("utf-8")
+
+        # Get all recording IDs
+        file_ids = [m.strip() for m in FILE_IDS.findall(stdout)]
+        file_ids = [
+            file_id[2:] if file_id.startswith("f=") else file_id
+            for file_id in file_ids
+        ]
+
+        scored_speaker_times = np.array(
+            [float(m) for m in SCORED_SPEAKER_TIME.findall(stdout)]
+        )
+
+        miss_speaker_times = np.array(
+            [float(m) for m in MISS_SPEAKER_TIME.findall(stdout)]
+        )
+
+        fa_speaker_times = np.array(
+            [float(m) for m in FA_SPEAKER_TIME.findall(stdout)]
+        )
+
+        error_speaker_times = np.array(
+            [float(m) for m in ERROR_SPEAKER_TIME.findall(stdout)]
+        )
+
+        with np.errstate(invalid="ignore", divide="ignore"):
+            tot_error_times = (
+                miss_speaker_times + fa_speaker_times + error_speaker_times
+            )
+            miss_speaker_frac = miss_speaker_times / scored_speaker_times
+            fa_speaker_frac = fa_speaker_times / scored_speaker_times
+            sers_frac = error_speaker_times / scored_speaker_times
+            ders_frac = tot_error_times / scored_speaker_times
+
+        # Values in percentage of scored_speaker_time
+        miss_speaker = rectify(miss_speaker_frac)
+        fa_speaker = rectify(fa_speaker_frac)
+        sers = rectify(sers_frac)
+        ders = rectify(ders_frac)
+
+        if individual_file_scores:
+            return miss_speaker, fa_speaker, sers, ders
+        else:
+            return miss_speaker[-1], fa_speaker[-1], sers[-1], ders[-1]

From 03a5750276950176d72f0d1a997fb17c19511d48 Mon Sep 17 00:00:00 2001
From: qingen <qingenz123@126.com>
Date: Fri, 14 Jan 2022 16:32:05 +0800
Subject: [PATCH 2/9] [vector] add DER scripts to calculate Diarization Error
 Rate

---
 utils/DER.py     |   31 +-
 utils/md-eval.pl | 2938 ++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 2967 insertions(+), 2 deletions(-)
 create mode 100755 utils/md-eval.pl

diff --git a/utils/DER.py b/utils/DER.py
index 4c67c4c7b..25003b0a4 100755
--- a/utils/DER.py
+++ b/utils/DER.py
@@ -4,11 +4,13 @@ False Alarm (FA), and Speaker Error Rate (SER) using md-eval-22.pl from NIST RT
 Authors
  * Neville Ryant 2018
  * Nauman Dawalatabad 2020
+ * Qingen Zhao 2021
 
 Credits
  This code is adapted from https://github.com/nryant/dscore
 """
-
+import argparse
+from distutils.util import strtobool
 import os
 import re
 import subprocess
@@ -84,7 +86,7 @@ def DER(
     """
 
     curr = os.path.abspath(os.path.dirname(__file__))
-    mdEval = os.path.join(curr, "../../tools/der_eval/md-eval.pl")
+    mdEval = os.path.join(curr, "./md-eval.pl")
 
     cmd = [
         mdEval,
@@ -150,3 +152,28 @@ def DER(
             return miss_speaker, fa_speaker, sers, ders
         else:
             return miss_speaker[-1], fa_speaker[-1], sers[-1], ders[-1]
+
+if __name__ == '__main__':
+
+    parser = argparse.ArgumentParser(description='Compute Diarization Error Rate')
+    parser.add_argument(
+        '--ref_rttm', required=True, help='the path of reference/groundtruth RTTM file')
+    parser.add_argument(
+        '--sys_rttm', required=True, help='the path of the system generated RTTM file')
+    parser.add_argument(
+        '--individual_file',
+        default=False,
+        type=strtobool,
+        help='if True, returns scores for each file in order')
+    parser.add_argument(
+        '--collar', default=0.25, type=float, help='forgiveness collar')
+    parser.add_argument(
+        '--ignore_overlap',
+        default=False,
+        type=strtobool,
+        help='if True, ignores overlapping speech during evaluation')
+    args = parser.parse_args()
+    print(args)
+
+    der = DER(args.ref_rttm, args.sys_rttm)
+    print("miss_speaker: %.3f%% fa_speaker: %.3f%% sers: %.3f%% ders: %.3f%%" % (der[0], der[1], der[2], der[-1]))
\ No newline at end of file
diff --git a/utils/md-eval.pl b/utils/md-eval.pl
new file mode 100755
index 000000000..0356b927f
--- /dev/null
+++ b/utils/md-eval.pl
@@ -0,0 +1,2938 @@
+#!/usr/bin/perl -w
+#################################
+# NIST. (2009). The 2009 (RT-09) Rich Transcription Meeting Recognition Evaluation Plan.
+# https://web.archive.org/web/20100606041157if_/http://www.itl.nist.gov/iad/mig/tests/rt/2009/docs/rt09-meeting-eval-plan-v2.pdf
+# Source (dscore): https://github.com/nryant/dscore/blob/master/scorelib/md-eval-22.pl
+#################################
+# BSD 2-Clause License
+#
+# Copyright (c) 2018, Neville Ryant
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+# * Redistributions of source code must retain the above copyright notice, this
+#   list of conditions and the following disclaimer.
+#
+# * Redistributions in binary form must reproduce the above copyright notice,
+#   this list of conditions and the following disclaimer in the documentation
+#   and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+#################################
+
+use strict;
+
+my $version = "22";
+
+#################################
+# History:
+#
+# version 22:  * JGF: added an option '-m FILE' to hold a CSV speaker map file.
+#
+# version 21:  * JGF: added a flag '-n' to not remove the directory paths from the source
+#                files in the UEM file.
+#
+# version 20:  * change metadata discard rule:  rather than discard if the midpoint
+#                (or endpoint) of the metadata object lies in a no-eval zone, discard
+#                if there is ANY overlap whatsoever between the metadata object and
+#                a no-eval zone.  This holds for system output objects only if the
+#                system output metadata object is not mapped to a ref object.
+#              * optimize IP and SU mapping by giving a secondary bonus mapping score
+#                to candidate ref-sys MD map pairs if the end-words of both coincide.
+#
+# version 19:  * bug fix in subroutine speakers_match
+#              * bug fix in tag_ref_words_with_metadata_info
+#
+# version 18:  * cosmetic fix to error message in eval_condition
+#              * added conditional output options for word coverage performance
+#              * added secondary MD word coverage optimization to word alignment
+#              * further optimize word alignment by considering MD subtypes
+#              * further optimize MD alignment by considering MD subtypes
+#              * add a new SU discard rule:  discard if TEND in no-eval zone
+#              * enforce legal values for su_extent_limit
+#
+# version 17:  create_speaker_segs modified to accommodate the same speaker
+#              having multiple overlapping speaker segments.  (This is an
+#              error and pathological condition, but the system must either
+#              disallow (abort on) the condition, or perform properly under
+#              the pathological condition.  The second option is chosen.)
+#
+# version 16:  * If neither -w nor -W is specified, suppress warnings about
+#                ref SPEAKER records subsuming no lexemes.
+#              * Output the overall speaker diarization stats after the
+#                stats for the individual files
+#              * Do not alter the case of alphabetic characters in the filename
+#                field from the ref rttm file
+#              * Made the format of the overall speaker error line more similar to
+#                the corresponding line of output from SpkrSegEval, to facilitate
+#                use of existing "grep" commands in existing scripts.
+#
+# version 15:  * bug fix in create_speaker_segs to accommodate
+#                contiguous same-speaker segments
+#              * added conditional file/channel scoring to
+#                speaker diarization evaluation
+#
+# version 14:  bug fix in md_score
+#
+# version 13:  add DISCOURSE_RESPONSE as a FILLER subtype
+#
+# version 12:  make REF LEXEMES optional if they aren't required
+#
+# version 11:  change default for noscore MD regions
+#
+# version 10:  bug fix
+#
+# version 09:
+#    * avoid crash when metadata discard yields no metadata
+#    * make evaluated ref_wds sensitive to metadata type
+#    * defer discarding of system output metadata until after
+#      metadata mapping, then discard only unmapped events.
+#    * extend 1-speaker scoring inhibition to metadata
+#    * eliminate demand for SPKR-INFO subtype for speakers
+#    * correct ref count of IP and SU exact boundary words
+#    * add official RT-04F scores
+#    * add conditional analyses for file/chnl/spkr/gender
+#
+# version 08:
+#    * bug fixes speaker diarization scoring
+#      - count of EVAL_WORDS corrected
+#      - no-score extended to nearest SPEAKER boundary
+#
+# version 07:
+#    * warning issued when discarding metadata events
+#      that cover LEXEMEs in the evaluation region
+#
+# version 06:
+#    * eliminated unused speakers from speaker scoring
+#    * changed discard algorithm for unannotated SU's and
+#      complex EDIT's to discard sys SU's and EDIT's when
+#      their midpoints overlap (rather than ANY overlap).
+#    * fixed display_metadata_mapping
+#
+# version 05:
+#    * upgraded display_metadata_mapping
+#
+# version 04:
+#    * diagnostic metadata mapping output added
+#    * uem_from_rttm bug fix
+#
+# version 03:
+#    * adjusted times used for speaker diarization
+#    * changed usage of max_extend to agree with cookbook
+#
+# version 02: speaker diarization evaluation added
+#
+# version 01: a merged version of df-eval-v14 and su-eval-v16
+#
+#################################
+
+#global data
+my $epsilon = 1E-8;
+my $miss_name = "  MISS";
+my $fa_name = "  FALSE ALARM";
+my %rttm_datatypes = (SEGMENT        => {eval => 1, "<na>" => 1},
+		      NOSCORE        => {"<na>" => 1},
+		      NO_RT_METADATA => {"<na>" => 1},
+		      LEXEME         => {lex => 1, fp => 1, frag => 1, "un-lex" => 1,
+					 "for-lex" => 1, alpha => 1, acronym => 1,
+					 interjection => 1, propernoun => 1, other => 1},
+		      "NON-LEX"      => {laugh => 1, breath => 1, lipsmack => 1,
+					 cough => 1, sneeze => 1, other => 1},
+		      "NON-SPEECH"   => {noise => 1, music => 1, other => 1},
+		      FILLER         => {filled_pause => 1, discourse_marker => 1,
+					 discourse_response => 1, explicit_editing_term => 1,
+					 other => 1},
+		      EDIT           => {repetition => 1, restart => 1, revision => 1,
+					 simple => 1, complex => 1, other => 1},
+		      IP             => {edit => 1, filler => 1, "edit&filler" => 1,
+					 other => 1},
+		      SU             => {statement => 1, backchannel => 1, question => 1,
+					 incomplete => 1, unannotated => 1, other => 1},
+		      CB             => {coordinating => 1, clausal => 1, other => 1},
+		      "A/P"          => {"<na>" => 1},
+		      SPEAKER        => {"<na>" => 1},
+		      "SPKR-INFO"    => {adult_male => 1, adult_female => 1, child => 1, unknown => 1});
+my %md_subtypes = (FILLER => $rttm_datatypes{FILLER},
+		   EDIT   => $rttm_datatypes{EDIT},
+		   IP     => $rttm_datatypes{IP},
+		   SU     => $rttm_datatypes{SU});
+my %spkr_subtypes = (adult_male => 1, adult_female => 1, child => 1, unknown => 1);
+
+my $noeval_mds = {
+    DEFAULT => {
+	NOSCORE        => {"<na>" => 1},
+	NO_RT_METADATA => {"<na>" => 1},
+    },
+};
+my $noscore_mds = {
+    DEFAULT => {
+	NOSCORE        => {"<na>" => 1},
+	LEXEME         => {"un-lex" => 1},
+	SU             => {unannotated => 1},
+    },
+    MIN => {
+	NOSCORE        => {"<na>" => 1},
+	SU             => {unannotated => 1},
+    },
+    FRAG_UNLEX => {
+	NOSCORE        => {"<na>" => 1},
+	LEXEME         => {frag => 1, "un-lex" => 1},
+	SU             => {unannotated => 1},
+    },
+    FRAG => {
+	NOSCORE        => {"<na>" => 1},
+	LEXEME         => {frag => 1},
+	SU             => {unannotated => 1},
+    },
+    NONE => {
+    },
+};
+my $noeval_sds = {
+    DEFAULT => {
+	NOSCORE        => {"<na>" => 1},
+    },
+};
+my $noscore_sds = {
+    DEFAULT => {
+	NOSCORE        => {"<na>" => 1},
+	"NON-LEX"      => {laugh => 1, breath => 1, lipsmack => 1,
+			   cough => 1, sneeze => 1, other => 1},
+    },
+};
+
+my %speaker_map;
+
+my $default_extend = 0.50; #the maximum time (in seconds) to extend a no-score zone
+my $default_collar = 0.00; #the no-score collar (in +/- seconds) to attach to SPEAKER boundaries
+my $default_tgap = 1.00; #the max gap (in seconds) between matching ref/sys words
+my $default_Tgap = 1.00; #the max gap (in seconds) between matching ref/sys metadata events
+my $default_Wgap = 0.10; #the max gap (in words) between matching ref/sys metadata events
+my $default_su_time_limit = 0.50; #the max extent (in seconds) to match for SU's
+my $default_su_word_limit = 2.00; #the max extent (in words) to match for SU's
+my $default_word_delta_score = 10.0; #the max delta score for word-based DP alignment of ref/sys words
+my $default_time_delta_score = 1.00; #the max delta score for time-based DP alignment of ref/sys words
+
+my $usage = "\n\nUsage: $0 [-h] -r <ref_file> -s <src_file>\n\n".
+    "Description:  md-eval evaluates EARS metadata detection performance\n".
+    "      by comparing system metadata output data with reference data\n".
+    "INPUT:\n".
+    "  -R <ref-list>  A file containing a list of the reference metadata files\n".
+    "       being evaluated, in RTTM format.  If the word-mediated alignment\n".
+    "       option is used then this data must include reference STT data\n".
+    "       in addition to the metadata being evaluated.\n".
+    "  OR\n".
+    "  -r <ref-file>  A file containing reference metadata, in RTTM format\n\n".
+    "  -S <sys-list>  A file containing a list of the system output metadata\n".
+    "       files to be evaluated, in RTTM format.  If the word-mediated\n".
+    "       alignment option is used then this data must include system STT\n".
+    "       output data in addition to the metadata to be evaluated.\n".
+    "  OR\n".
+    "  -s <sys-file>  A file containing system output metadata, in RTTM format\n\n".
+    "  input options:\n".
+    "    -x to include complex edits in the analysis and scoring.\n".
+    "    -w for word-mediated alignment.\n".
+    "       * The default (time-mediated) alignment aligns ref and sys metadata\n".
+    "         according to the time overlap of the original ref and sys metadata\n".
+    "         time intervals.\n".
+    "       * Word-mediated alignment aligns ref and sys metadata according to\n".
+    "         the alignment of the words that are subsumed within the metadata\n".
+    "         time intervals.\n".
+    "    -W for word-optimized mapping.\n".
+    "       * The default (time-optimized) mapping maps ref and sys metadata\n".
+    "         so as to maximize the time overlap of mapped metadata events.\n".
+    "       * Word-optimized mapping maps ref and sys metadata so as to\n".
+    "         maximize the overlap in terms of the number of reference words\n".
+    "         that are subsumed within the overlapping time interval.\n".
+    "    -a <cfgs> Conditional analysis options for metadata detection performance:\n".
+    "         c for performance versus channel,\n".
+    "         f for performance versus file,\n".
+    "         g for performance versus gender, and\n".
+    "         s for performance versus speaker.\n".
+    "    -A <cf> Conditional analysis options for word coverage performance:\n".
+    "         c for performance versus channel,\n".
+    "         f for performance versus file,\n".
+    "    -t <time gap> The maximum time gap allowed between matching reference\n".
+    "       and system output words (in seconds).  Default value is $default_tgap.\n".
+    "    -T <time gap> The maximum time gap allowed between matching reference\n".
+    "       and system output metadata (in seconds).  Default value is $default_Tgap.\n".
+    "    -l <SU extent limit>  The maximum SU extent used to compute overlap\n".
+    "       between reference and system output SU's.  For time-optimized SU\n".
+    "       mapping this is the maximum time extent.  For word-optimized SU\n".
+    "       mapping (using the -W option) this is the maximum number of words.\n".
+    "       SU extent is limited to the last part of the SU. Default value is\n".
+    "       $default_su_time_limit for time-optimized mapping, $default_su_word_limit for word-optimized mapping.\n".
+    "    -u <uem-file> A file containing the evaluation partitions,\n".
+    "       in UEM format.\n".
+    "    -g <glm-file> A file containing word transformations used to\n".
+    "       standardize the representation of words.\n".
+    "    -o to include overlapping speech in MD evaluation.  With this option,\n".
+    "       separate recognition passes are made for each reference speaker.\n".
+    "    -c <collar> is the no-score zone around reference speaker segment\n".
+    "       boundaries.  (Speaker Diarization output is not evaluated within\n".
+    "       +/- collar seconds of a reference speaker segment boundary.)\n".
+    "       Default value is $default_collar seconds.\n".
+    "    -1 to limit scoring to those time regions in which only a single\n".
+    "       speaker is speaking\n".
+    "    -y <name> to select named no-eval conditions for metadata\n".
+    "    -Y <name> to select named no-score conditions for metadata\n".
+    "    -z <name> to select named no-eval conditions for speaker diarization\n".
+    "    -Z <name> to select named no-score conditions for speaker diarization\n".
+    "    -e to examine metadata mapping\n".
+    "    -d to print word alignment and error calculation details\n".
+    "    -D to print metadata event alignment and error calculation details\n".
+    "    -m to print speaker mapping details for speaker diarization\n".
+    "    -M FILE to print speaker mapping details for speaker diarization to a CSV file called 'FILE'\n".
+    "    -v to print the event sequence for each diarization source file\n".
+    "    -n to keep the directory names of the UEM source file entries\n".
+    "OUTPUT:\n".
+    "  Performance statistics are written to STDOUT.\n".
+    "\n";
+
+######
+# Intro
+my ($date, $time) = date_time_stamp();
+print "command line (run on $date at $time) Version: $version  ", $0, " ", join(" ", @ARGV), "\n";
+
+use vars qw ($opt_h $opt_w $opt_W $opt_d $opt_D $opt_R $opt_r $opt_S $opt_s $opt_l $opt_c $opt_x);
+use vars qw ($opt_t $opt_T $opt_g $opt_p $opt_P $opt_o $opt_a $opt_A $opt_u $opt_1 $opt_m $opt_v $opt_e);
+use vars qw ($opt_y $opt_Y $opt_z $opt_Z $opt_n $opt_M);
+$opt_y = $opt_Y = $opt_z = $opt_Z = "DEFAULT";
+use Getopt::Std;
+getopts ('nhdDwWox1mvec:R:r:S:s:t:T:g:p:P:a:A:u:l:y:Y:z:Z:M:');
+not defined $opt_h or die
+    "\n$usage";
+defined $opt_r or defined $opt_R or die
+    "\nCOMMAND LINE ERROR:  no reference data specified$usage";
+not defined $opt_r or not defined $opt_R or die
+    "\nCOMMAND LINE ERROR:  both reference file list and reference file specified$usage";
+defined $opt_s or defined $opt_S or die
+    "\nCOMMAND LINE ERROR:  no system output data specified$usage";
+not defined $opt_s or not defined $opt_S or die
+    "\nCOMMAND LINE ERROR:  both system output file list and system output file specified$usage";
+my $word_gap = defined $opt_t ? $opt_t : $default_tgap;
+my $md_gap = $opt_W ? $default_Wgap : (defined $opt_T ? $opt_T : $default_Tgap);
+my $su_extent_limit = defined $opt_l ? $opt_l :
+    ($opt_W ? $default_su_word_limit : $default_su_time_limit);
+$opt_W ? ($su_extent_limit >= 1 or die "\nCOMMAND LINE ERROR:  SU extent limit must be at least 1 for word-based MD alignment$usage") :
+         ($su_extent_limit > 0 or die "\nCOMMAND LINE ERROR:  SU extent limit must be positive for time-based MD alignment$usage");
+my $max_wd_delta_score = $opt_w ? $default_word_delta_score : $default_time_delta_score;
+$max_wd_delta_score = $opt_p if defined $opt_p;
+my $max_md_delta_score = $opt_W ? $default_word_delta_score : $default_time_delta_score;
+$max_md_delta_score = $opt_P if defined $opt_P;
+my $collar = defined($opt_c) ? $opt_c : $default_collar;
+$collar >= 0 or die
+    "\nCOMMAND LINE ERROR:  Speaker Diarization scoring collar ('$collar') must be non-negative$usage";
+my $max_extend = $default_extend;
+$opt_a = "" unless defined $opt_a;
+$opt_A = "" unless defined $opt_A;
+start_speaker_map_file($opt_M) if $opt_M;
+
+my $noeval_md = eval_condition ($opt_y, $noeval_mds, "no-eval", "metadata");
+my $noscore_md = eval_condition ($opt_Y, $noscore_mds, "no-score", "metadata");
+my $noeval_sd = eval_condition ($opt_z, $noeval_sds, "no-score", "speaker diarization");
+my $noscore_sd = eval_condition ($opt_Z, $noscore_sds, "no-score", "speaker diarization");
+
+my %type_order = (NOSCORE        => 0,
+		  NO_RT_METADATA => 1,
+		  SEGMENT        => 2,
+		  SPEAKER        => 3,
+		  SU             => 4,
+		  "A/P"          => 5,
+		  "NON-SPEECH"   => 6,
+		  EDIT           => 7,
+		  FILLER         => 8,
+		  IP             => 9,
+		  CB             => 10,
+		  "NON-LEX"      => 11,
+		  LEXEME         => 12);
+my %event_order = (END => 0,
+		   MID => 1,
+		   BEG => 2);
+my %source_order = (REF => 0,
+		    SYS => 1);
+
+{
+    my (%ref, %sys, $glm, $uem);
+
+    print_parameters ();
+    ($glm) = get_glm_data ($opt_g);
+    get_rttm_file (\%ref, $opt_r, $glm);
+    get_rttm_data (\%ref, $opt_R, $glm);
+    get_rttm_file (\%sys, $opt_s, $glm);
+    get_rttm_data (\%sys, $opt_S, $glm);
+
+    ($uem) = get_uem_data ($opt_u, $opt_n);
+    evaluate (\%ref, \%sys, $uem);
+}
+
+exit 0;
+
+#################################
+
+sub eval_condition {
+
+    my ($name, $conditions, $exclusion, $evaluation) = @_;
+
+    $name = "DEFAULT" unless $name;
+    return $conditions->{$name} if defined $conditions->{$name};
+    print STDERR "\nCOMMAND LINE ERROR:  unknown name ($name) of $exclusion conditions for $evaluation\n".
+	"    available $exclusion conditions for $evaluation are:\n\n";
+    foreach $name (sort keys %$conditions) {
+	printf STDERR "%-24stype    subtype\n", "    for \"$name\":";
+	foreach my $type (sort keys %{$conditions->{$name}}) {
+	    foreach my $subt (sort keys %{$conditions->{$name}{$type}}) {
+		printf STDERR "%28s    %s\n", $type, $subt;
+	    }
+	}
+	print "\n";
+    }
+    die "$usage";
+}
+
+#################################
+
+sub print_parameters {
+
+    print $opt_w ? "\nWord-based metadata alignment, max gap between matching words = $word_gap sec\n" :
+	"\nTime-based metadata alignment\n";
+    print "\nMetadata evaluation parameters:\n";
+    $opt_W ? (print "    word-optimized metadata mapping\n".
+	            "        max gap between matching metadata events = $md_gap words\n".
+	            "        max extent to match for SU's = $su_extent_limit words\n") :
+	     (print "    time-optimized metadata mapping\n".
+		    "        max gap between matching metadata events = $md_gap sec\n".
+		    "        max extent to match for SU's = $su_extent_limit sec\n");
+    print "\nSpeaker Diarization evaluation parameters:\n".
+	  "    The max time to extend no-score zones for NON-LEX exclusions is $max_extend sec\n".
+	  "    The no-score collar at SPEAKER boundaries is $collar sec\n";
+    printf "\nExclusion zones for evaluation and scoring are:\n".
+	   "                             -----MetaData-----        -----SpkrData-----\n".
+	   "     exclusion set name:%12s%11s%15s%11s\n".
+	   "     token type/subtype      no-eval   no-score        no-eval   no-score\n",
+	       $opt_y, $opt_Y, $opt_z, $opt_Z;
+    print  "             (UEM)              X                         X\n";
+    foreach my $type (sort keys %rttm_datatypes) {
+	foreach my $subt (sort keys %{$rttm_datatypes{$type}}) {
+	    next unless ($noeval_md->{$type}{$subt} or
+			 $noscore_md->{$type}{$subt} or
+			 $noeval_sd->{$type}{$subt} or
+			 $noscore_sd->{$type}{$subt});
+	    printf "%15s/%-14s", $type, $subt;
+	    printf "%3s", $noeval_md->{$type}{$subt} ? "X" : "";
+	    printf "%10s", $noscore_md->{$type}{$subt} ? "X" : "";
+	    printf "%16s", $noeval_sd->{$type}{$subt} ? "X" : "";
+	    printf "%10s\n", $noscore_sd->{$type}{$subt} ? "X" : "";
+	}
+    }
+}
+
+#################################
+
+sub get_glm_data {
+
+    my ($file) = @_;
+    my ($record, @fields, $word, %words, %data);
+
+    return unless defined $file;
+    open DATA, $file or die
+	"\nCOMMAND LINE ERROR:  unable to open glm file '$file'$usage";
+    while ($record = <DATA>) {
+	next if $record =~ /^\s*$/;
+	next if $record =~ /^\s*(\[|\*|\%|\;)/;
+        @fields = split /\s+=>\s+/, lc $record;
+	shift @fields if $fields[0] eq "";
+        next unless @fields > 1;
+	$fields[0] =~ s/^\s+//;
+        $fields[1] =~ s/[^a-z-'_ \.].*//;
+        next if $fields[0] =~ /^\s*$/ or $fields[1] =~ /^\s*$/;
+        $data{$fields[0]} = [split /\s+/, $fields[1]];
+    }
+    close DATA;
+    return {%data};
+}
+
+#################################
+
+sub get_uem_data {
+
+    my ($file, $keepDirectoryPath) = @_;
+    my ($record, @fields, $seg, $chnl, %data);
+
+    return unless defined $file;
+    open DATA, $file or die
+	"\nCOMMAND LINE ERROR:  unable to open uem file '$file'$usage";
+    while ($record = <DATA>) {
+	next if $record =~ /^\s*[\#;]|^\s*$/;
+	@fields = split /\s+/, $record;
+	shift @fields if $fields[0] eq "";
+	@fields >= 4 or die
+	    ("\n\nFATAL ERROR:  insufficient number of fields in UEM record\n".
+	     "    record is: '$record'\n\n");
+	undef $seg;
+	$seg->{FILE} = shift @fields;
+	$seg->{CHNL} = lc shift @fields;
+	$seg->{TBEG} = lc shift @fields;
+	$seg->{TEND} = lc shift @fields;
+        $seg->{FILE} =~ s/.*\/// if (! $keepDirectoryPath);      #strip directory
+        $seg->{FILE} =~ s/\.[^.]*//;   #strip file type
+        $seg->{TBEG} =~ s/[^0-9\.]//g; #strip non-numeric (commas)
+        $seg->{TEND} =~ s/[^0-9\.]//g; #strip non-numeric (commas)
+	push @{$data{$seg->{FILE}}{$seg->{CHNL}}}, $seg;
+    }
+    close DATA;
+
+#sort and check data
+    foreach $file (keys %data) {
+	foreach $chnl (keys %{$data{$file}}) {
+	    @{$data{$file}{$chnl}} =
+		sort {$a->{TBEG} <=> $b->{TBEG}} @{$data{$file}{$chnl}};
+	    my $prev_seg;
+	    foreach $seg (@{$data{$file}{$chnl}}) {
+		$seg->{TEND} > $seg->{TBEG} or die
+		    "\n\nFATAL ERROR:  non-positive evaluation segment length in UEM data for file $file, channel $chnl\n\n";
+		not defined $prev_seg or $seg->{TBEG} >= $prev_seg->{TEND} or die
+		    ("\n\nFATAL ERROR:  UEM file has overlapping evaluation segments\n".
+		     "    file $file, channel $chnl:  ($prev_seg->{TBEG},$prev_seg->{TEND}),".
+		     " ($seg->{TBEG},$seg->{TEND})\n\n");
+		$prev_seg = $seg;
+	    }
+	}
+    }
+    return {%data};
+}
+
+#################################
+
+sub get_rttm_data {
+
+    my ($data, $list, $glm) = @_;
+
+    return unless defined $list;
+    open LIST, $list or die
+	"\nCOMMAND LINE ERROR:  unable to open file list '$list'$usage";
+    while (my $file = <LIST>) {
+	get_rttm_file ($data, $file, $glm);
+    }
+    close LIST;
+}
+
+#################################
+
+sub get_rttm_file {
+
+    my ($data, $rttm_file, $glm) = @_;
+    my ($record, @fields, $data_type, $file, $chnl, $word, @words, $token);
+
+    return unless defined $rttm_file;
+    open DATA, $rttm_file or die
+	"\nCOMMAND LINE ERROR:  unable to open RTTM file '$rttm_file'$usage";
+    while ($record = <DATA>) {
+	next if $record =~ /^\s*[\#;]|^\s*$/;
+	@fields = split /\s+/, $record;
+	shift @fields if $fields[0] eq "";
+	@fields >= 9 or die
+	    ("\n\nFATAL ERROR:  insufficient number of fields in RTTM file '$rttm_file'\n".
+	     "    input RTTM record is: '$record'\n\n");
+	$data_type = uc shift @fields;
+	undef $token;
+	$token->{TYPE} = $data_type;
+	$token->{FILE} = $file = shift @fields;
+	$token->{CHNL} = $chnl = lc shift @fields;
+	$token->{TBEG} = lc shift @fields;
+	$token->{TBEG} =~ s/\*//;
+	$token->{TDUR} = lc shift @fields;
+	$token->{TDUR} =~ s/\*//;
+	$token->{TDUR} = 0 if $token->{TDUR} eq "<na>";
+	$token->{TDUR} >= 0 or die
+	    ("\n\nFATAL ERROR -- negative metadata duration in file $file,'\n".
+	     "    input RTTM record is: '$record'\n\n");
+	$token->{WORD} = lc shift @fields;
+	$token->{SUBT} = lc shift @fields;
+	$rttm_datatypes{$token->{TYPE}}{$token->{SUBT}} or die
+	    ("\n\nFATAL ERROR:  unknown RTTM data type/subtype ('$token->{TYPE}'/'$token->{SUBT}') in file $rttm_file\n".
+	     "    input RTTM record is: '$record'\n\n");
+	$token->{SPKR} = shift @fields;
+	$token->{CONF} = lc shift @fields;
+	$token->{CONF} = "-"       unless defined $token->{CONF};
+	$token->{SPKR} = "<na>" unless defined $token->{SPKR};
+	if ($data_type eq "SPKR-INFO") {
+	    not defined $data->{$file}{$chnl}{$data_type}{$token->{SPKR}} or die
+		("\n\nFATAL ERROR:  multiple $data_type records for speaker $token->{SPKR} in file $file\n".
+		 "    input RTTM record is: '$record'\n\n");
+	    defined $spkr_subtypes{$token->{SUBT}} or die
+		("\n\nFATAL ERROR:  unknown $data_type subtype ($token->{SUBT}) in file '$file'\n".
+		 "    input RTTM record is: '$record'\n\n");
+	    $data->{$file}{$chnl}{$data_type}{$token->{SPKR}}{GENDER} = $token->{SUBT};
+	}
+	else {
+	    $token->{TEND} = $token->{TBEG}+$token->{TDUR};
+	    $token->{TMID} = $token->{TBEG}+$token->{TDUR}/2;
+	}
+
+	if ($data_type eq "LEXEME") {
+	    $token->{WTYP} = ($token->{SUBT} =~ /^fp$/         ? "fp"      :
+			      ($token->{SUBT} =~ /^frag$/      ? "frag"    :
+			       ($token->{SUBT} =~ /^un-lex$/   ? "un-lex"  :
+				($token->{SUBT} =~ /^for-lex$/ ? "for-lex" : "lex"))));
+	    @words = standardize_word ($token, $glm);
+	    foreach $word (@words) {
+		push @{$data->{$file}{$chnl}{LEXEME}}, $word;
+		push @{$data->{$file}{$chnl}{RTTM}}, $word;
+	    }
+	}
+	elsif ($data_type eq "SPEAKER") {
+	    push @{$data->{$file}{$chnl}{SPEAKER}{$token->{SPKR}}}, $token;
+	    push @{$data->{$file}{$chnl}{RTTM}}, $token;
+	}
+	elsif ($md_subtypes{$token->{TYPE}}) {
+	    defined $md_subtypes{$token->{TYPE}}{$token->{SUBT}} or die
+		("\n\nFATAL ERROR:  unknown $data_type subtype ($token->{SUBT}) in file '$file'\n".
+		 "    input RTTM record is: '$record'\n\n");
+	    push @{$data->{$file}{$chnl}{$data_type}}, $token;
+	    push @{$data->{$file}{$chnl}{RTTM}}, $token;
+	}
+	elsif ($data_type ne "SPKR-INFO") {
+	    push @{$data->{$file}{$chnl}{RTTM}}, $token;
+	}
+    }
+    close DATA;
+
+#sort and check data
+    foreach $file (keys %$data) {
+	foreach $chnl (keys %{$data->{$file}}) {
+	    foreach $data_type (keys %{$data->{$file}{$chnl}}) {
+		next if $data_type eq "SPKR-INFO";
+		if ($data_type eq "SPEAKER") {
+		    foreach my $spkr (keys %{$data->{$file}{$chnl}{$data_type}}) {
+			my $gender = $data->{$file}{$chnl}{"SPKR-INFO"}{$spkr}{GENDER};
+			$gender = $data->{$file}{$chnl}{"SPKR-INFO"}{$spkr}{GENDER} = "unknown" if not $gender;
+			@{$data->{$file}{$chnl}{$data_type}{$spkr}} =
+			    sort {$a->{TMID}<=>$b->{TMID}} @{$data->{$file}{$chnl}{$data_type}{$spkr}};
+			my $prev_token;
+			foreach $token (@{$data->{$file}{$chnl}{$data_type}{$spkr}}) {
+			    $token->{SUBT} = $gender;
+			    next unless $prev_token;
+			    not $prev_token or $token->{TBEG} >= $prev_token->{TEND}-$epsilon or die
+				("\n\nFATAL ERROR:  RTTM file has overlapping $data_type tokens for speaker $spkr\n".
+				 "    in file $file, channel $chnl:  ($prev_token->{TBEG},$prev_token->{TEND}),".
+				 " ($token->{TBEG},$token->{TEND})\n\n");
+			    $prev_token = $token;
+			}
+		    }
+		}
+		else {
+		    @{$data->{$file}{$chnl}{$data_type}} =
+			sort {$a->{TMID} <=> $b->{TMID}} @{$data->{$file}{$chnl}{$data_type}};
+		}
+	    }
+	}
+    }
+}
+
+#################################
+
+sub evaluate {
+
+    my ($ref_data, $sys_data, $uem_data) = @_;
+    my ($uem, $uem_sd_eval, $uem_sd_score, $uem_md_eval, $uem_md_score);
+    my ($ref_wds, $sys_wds, $ref_mds, $sys_mds, $type, %scores, $ref_rttm, $sys_rttm);
+
+    foreach my $file (sort keys %$ref_data) {
+	foreach my $chnl (sort keys %{$ref_data->{$file}}) {
+	    $ref_rttm = $ref_data->{$file}{$chnl}{RTTM};
+	    $sys_rttm = $sys_data->{$file}{$chnl}{RTTM};
+	    $ref_wds = $ref_data->{$file}{$chnl}{LEXEME} ? $ref_data->{$file}{$chnl}{LEXEME} : [];
+	    $sys_wds = $sys_data->{$file}{$chnl}{LEXEME} ? $sys_data->{$file}{$chnl}{LEXEME} : [];
+	    $uem = $uem_data->{$file}{$chnl};
+	    $uem = uem_from_rttm ($ref_rttm) if not defined $uem;
+	    @$ref_wds > 0 or not $opt_w or die
+		"\n\nFATAL ERROR:  no reference words for file '$file' and channel '$chnl'\n\n";
+	    @$sys_wds > 0 or not $opt_w or die
+		"\n\nFATAL ERROR:  no system output words for file '$file' and channel '$chnl'\n".
+		    "              Words are required for word-mediated alignment\n\n";
+	    if ($ref_wds and ($opt_w or $opt_e)) {
+	        tag_words_with_metadata_attributes ($ref_rttm, $ref_wds);
+	        tag_words_with_metadata_attributes ($sys_rttm, $sys_wds);
+	        perform_word_alignment ($file, $chnl, $ref_wds, $sys_wds, $uem);
+	    }
+	    $uem_md_eval = add_exclusion_zones_to_uem ($noeval_md, $uem, $ref_rttm);
+	    $uem_md_score = add_exclusion_zones_to_uem ($noscore_md, $uem_md_eval, $ref_rttm);
+	    $uem_md_score = exclude_overlapping_speech_from_uem ($uem_md_score, $ref_rttm) if $opt_1;
+ 	    tag_scoreable_words ($ref_wds, $uem_md_score);
+	    foreach $type (sort keys %md_subtypes) {
+		$ref_mds = $ref_data->{$file}{$chnl}{$type};
+		next unless defined $ref_mds;
+		@$ref_wds > 0 or die
+		    "\n\nFATAL ERROR:  no reference words for file '$file' and channel '$chnl'\n\n";
+		$sys_mds = $sys_data->{$file}{$chnl}{$type};
+		$sys_mds = $sys_data->{$file}{$chnl}{$type} = [] unless defined $sys_mds;
+		map_metadata_to_words ($sys_mds, $sys_wds, $ref_mds, $ref_wds);
+		discard_unevaluated_metadata ($uem_md_eval, $type, $ref_mds, $ref_wds, "REF");
+		next if @$ref_mds == 0;
+		align_data ($ref_mds, $sys_mds, "", \&md_score, $max_md_delta_score);
+		trace_best_path ($ref_mds, $sys_mds);
+		discard_metadata_subtype ("EDIT", "complex", $ref_mds, $sys_mds) if $type eq "EDIT" and $opt_x;
+		discard_metadata_subtype ("SU", "unannotated", $ref_mds, $sys_mds) if $type eq "SU";
+		discard_unevaluated_metadata ($uem_md_eval, $type, $sys_mds, $ref_wds, "SYS");
+		($scores{$type}{$file}{$chnl}) = score_metadata_path
+		    ($type, $file, $chnl, $ref_mds, $sys_mds, $ref_wds);
+	    }
+
+	    $ref_mds = $ref_data->{$file}{$chnl}{SPEAKER};
+	    if (defined $ref_mds) {
+		@$ref_wds > 0 or not $opt_W or die
+		    "\n\nFATAL ERROR:  no reference words for file '$file' and channel '$chnl'\n\n";
+		$uem_sd_eval = add_exclusion_zones_to_uem ($noeval_sd, $uem, $ref_rttm);
+		$sys_mds = $sys_data->{$file}{$chnl}{SPEAKER};
+		$sys_mds = $sys_data->{$file}{$chnl}{SPEAKER} = {} unless defined $sys_mds;
+		map_spkrdata_to_words ($sys_mds, $sys_wds, $ref_mds, $ref_wds);
+		($scores{SPEAKER}{$file}{$chnl}) = score_speaker_diarization
+		    ($file, $chnl, $ref_mds, $sys_mds, $ref_wds, $uem_sd_eval, $ref_rttm);
+	    }
+
+	    if ($opt_e) {
+		discard_unevaluated_metadata ($uem, "LEXEME", $ref_rttm);
+		discard_unevaluated_metadata ($uem, "LEXEME", $sys_rttm);
+		discard_unevaluated_metadata ($uem_md_eval, "", $ref_rttm);
+		discard_metadata_subtype ("EDIT", "complex", $ref_rttm, $sys_rttm) if $opt_x;
+		discard_metadata_subtype ("SU", "unannotated", $ref_rttm, $sys_rttm);
+		discard_unevaluated_metadata ($uem_md_eval, "", $sys_rttm);
+		display_metadata_mapping ($file, $chnl, $ref_rttm, $sys_rttm, $ref_wds);
+	    }
+	}
+    }
+
+    foreach $type (sort keys %md_subtypes) {
+	md_performance_analysis ($type, $scores{$type}, $md_subtypes{$type}, $ref_data)
+	    if $scores{$type};
+    }
+    sd_performance_analysis ($scores{SPEAKER}, \%spkr_subtypes)
+	if $scores{SPEAKER};
+}
+
+#################################
+
+sub perform_word_alignment {
+
+    my ($file, $chnl, $ref_wds, $sys_wds, $uem) = @_;
+
+    my @ref_wds = @$ref_wds;
+    my @sys_wds = @$sys_wds;
+    discard_unevaluated_words ($uem, \@ref_wds);
+    discard_unevaluated_words ($uem, \@sys_wds);
+    @ref_wds > 0 or die
+	"\n\nFATAL ERROR:  no reference words in UEM portion of file '$file' and channel '$chnl'\n\n";
+    @sys_wds > 0 or not $opt_w or die
+	"\n\nFATAL ERROR:  no system output words in UEM portion of file '$file' and channel '$chnl'\n".
+	    "              Words are required for word-mediated alignment\n\n";
+    return unless @sys_wds > 0;
+
+    if ($opt_o) {
+	foreach my $spkr (word_kinds ($ref_wds, "SPKR")) {
+	    align_data ($ref_wds, $sys_wds, $spkr, \&word_score, $max_wd_delta_score);
+	    trace_best_path ($ref_wds, $sys_wds, $spkr);
+	}
+	decide_who_spoke_the_words ($ref_wds, $sys_wds);
+    }
+    else {
+	align_data ($ref_wds, $sys_wds, "", \&word_score, $max_wd_delta_score);
+	trace_best_path ($ref_wds, $sys_wds);
+    }
+
+#map system output word times to ref words
+    foreach my $wd (@$sys_wds) {
+	$wd->{RTBEG} = adjust_sys_time_to_ref ($wd->{TBEG}, $sys_wds);
+	$wd->{RTEND} = adjust_sys_time_to_ref ($wd->{TEND}, $sys_wds);
+	$wd->{RTDUR} = $wd->{RTEND} - $wd->{RTBEG};
+	$wd->{RTMID} = $wd->{RTBEG} + $wd->{RTDUR}/2;
+    }
+    score_word_path ($file, $chnl, $ref_wds, $sys_wds) if $opt_d;
+}
+
+################################
+
+sub time_in_eval_partition {
+
+    my ($time, $uem_eval) = @_;
+
+    return 1 unless defined $uem_eval; #not using UEM partition specification
+    foreach my $partition (@$uem_eval) {
+	return 1 if event_covers_time ($partition, $time);
+    }
+    return 0;
+}
+
+#################################
+
+sub discard_unevaluated_words {
+
+    my ($uem, $wds) = @_;
+
+    for (my $index=0; $index<@$wds; $index++) {
+	splice (@$wds, $index--, 1)
+	    if ($wds->[$index]{TYPE} eq "LEXEME" and
+		not time_in_eval_partition ($wds->[$index]{TMID}, $uem));
+    }
+}
+
+#################################
+
+sub discard_unevaluated_metadata {
+
+    my ($uem_eval, $type, $mds, $ref_wds, $src) = @_;
+
+    for (my $index=0; $index<@$mds; $index++) {
+	my $md = $mds->[$index];
+	next if (($type and $md->{TYPE} ne $type) or
+		 (not $type and not $md_subtypes{$md->{TYPE}}) or
+		 $md->{MAPPTR} or
+		 md_in_uem ($md, $uem_eval));
+	warn_if_discarded_md_covers_scored_lexemes ($md, $ref_wds, $uem_eval, $src) if $ref_wds;
+	splice (@$mds, $index--, 1);
+    }
+}
+
+#################################
+
+sub warn_if_discarded_md_covers_scored_lexemes {
+
+    my ($md, $ref_wds, $uem, $source) = @_;
+    my ($wbeg, $wend, $index);
+
+    ($wbeg, $wend) = md_word_indices ($md, $ref_wds);
+
+    for ($index=$wbeg; $index<=$wend; $index++) {
+	next unless ($ref_wds->[$index]{SCOREABLE} and
+		     time_in_eval_partition ($ref_wds->[$index]{TMID}, $uem));
+	warn "\nWARNING:  A $source metadata event is being deleted that covers evaluated reference LEXEMEs\n".
+	    "    (type=$md->{TYPE}, subtype=$md->{SUBT}, spkr=$md->{SPKR}, TBEG=$md->{TBEG}, TEND=$md->{TEND})\n";
+	last;
+    }
+}
+
+#################################
+
+sub discard_metadata_subtype {
+
+    my ($type, $subtype, $ref_mds, $sys_mds) = @_;
+    my ($iref, $isys, $ref_md, $sys_md);
+
+#discard all sys $type events that map to a ref event with subtype = $subtype
+#or that are unmapped and have midpoints that lie within a ref event with subtype = $subtype
+    for ($iref=0; $iref<@$ref_mds; $iref++) {
+	$ref_md = $ref_mds->[$iref];
+	next unless ($ref_md->{TYPE} eq $type and
+		     $ref_md->{SUBT} eq $subtype);
+	for ($isys=0; $isys<@$sys_mds; $isys++) {
+	    $sys_md = $sys_mds->[$isys];
+	    splice (@$sys_mds, $isys--, 1)
+		if ($sys_md->{TYPE} eq $type and
+		    (($sys_md->{MAPPTR} and $sys_md->{MAPPTR}{SUBT} eq $subtype) or
+		     (not $sys_md->{MAPPTR} and event_covers_time ($ref_md, $sys_md->{RTMID}))));
+	}
+
+#discard all ref $type/$subtype events
+	splice (@$ref_mds, $iref--, 1);
+    }
+}
+
+#################################
+
+sub tag_scoreable_words {
+
+    my ($wds, $uem_eval) = @_;
+
+    foreach my $wd (@$wds) {
+	$wd->{SCOREABLE} = time_in_eval_partition ($wd->{TMID}, $uem_eval);
+    }
+}
+
+#################################
+
+sub tag_words_with_metadata_attributes {
+
+    my ($mds, $wds) = @_;
+    my ($md, $iwbeg, $iwend, $iw, $wd, $type);
+
+    foreach $md (@$mds) {
+	$type = $md->{TYPE};
+	next unless $type =~ /^(FILLER|EDIT|SU|IP)$/;
+	($iwbeg, $iwend) = md_word_indices ($md, $wds);
+	if ($type =~ /^(FILLER|EDIT)$/) {
+	    for ($iw=$iwbeg; $iw<=$iwend; $iw++) {
+		$wds->[$iw]{ATTRIBUTES}{$md->{TYPE}} = $md->{SUBT};
+	    }
+	}
+	elsif ($type =~ /^(SU|IP)$/) {
+	    $wds->[$iwend]{ATTRIBUTES}{$md->{TYPE}} = $md->{SUBT};
+	}
+    }
+    return;
+}
+
+#################################
+
+sub tag_ref_words_with_metadata_info {
+
+    my ($mds, $wds, $src) = @_;
+    my ($md, $iwbeg, $iwend, $iw, $type);
+
+    foreach $md (@$mds) {
+	$type = $md->{TYPE};
+	($iwbeg, $iwend) = $src eq "REF" ?
+	    ($md->{WBEG}, $md->{WEND}) : ($md->{RWBEG}, $md->{RWEND}) ;
+	if ($type =~ /^(FILLER|EDIT)$/) {
+	    for ($iw=max($iwbeg,0); $iw<=min($iwend,@$wds-1); $iw++) {
+		$wds->[$iw]{"$src-$type"}{$md->{SUBT}}{MAP}++;
+	    }
+	}
+	elsif ($type =~ /^(SU|IP)$/) {
+	    $iwend = min(max($iwend,0),@$wds-1);
+	    $wds->[$iwend]{"$src-$type"}{$md->{SUBT}}{defined $md->{MAPPTR} ? "MAP" : "NOT"}++;
+	}
+    }
+    return;
+}
+
+#################################
+
+sub md_performance_analysis {
+
+    my ($metadata_type, $counts, $subtypes, $ref_data) = @_;
+    my ($file, $chnl, $spkr, $word, $type, $type_counts, $key);
+    my (@files, @chnls, @spkrs, @types, %nevent, %nwerr);
+    my ($subtype, $sys_subtype, %nconf, %offsets);
+
+#compute marginal counts
+    @files = keys %$counts;
+    foreach $file (@files) {
+	@chnls = keys %{$counts->{$file}};
+	foreach $chnl (@chnls) {
+	    $type_counts = $counts->{$file}{$chnl};
+	    foreach $type ("REF", "DEL", "INS", "SUB") {
+	        next unless defined $type_counts->{WORDS}{$type};
+		$nwerr{ALL}{$type} += $type_counts->{WORDS}{$type};
+		$nwerr{"c=$chnl f=$file"}{$type} += $type_counts->{WORDS}{$type} if $opt_A =~ /c/i and $opt_A =~ /f/i;
+		$nwerr{"c=$chnl"}{$type} += $type_counts->{WORDS}{$type} if $opt_A =~ /c/i and not $opt_A =~ /f/i;
+		$nwerr{"f=$file"}{$type} += $type_counts->{WORDS}{$type} if $opt_A =~ /f/i and not $opt_A =~ /c/i;
+	    }
+	    foreach $type ("WBEG", "WEND") {
+		foreach $key (keys %{$type_counts->{WORD_OFFSET}{$type}}) {
+		    $offsets{ALL}{$type}{$key} += $type_counts->{WORD_OFFSET}{$type}{$key};
+		}
+	    }
+	    my $spkr_info = $ref_data->{$file}{$chnl}{"SPKR-INFO"};
+	    $spkr_info->{unknown}{GENDER} = "unknown" unless defined $spkr_info->{unknown};
+	    foreach $type (keys %$type_counts) {
+		next unless $type =~ /^(REF|DEL|INS|SUB|CONFUSION)$/;
+		@spkrs = keys %{$type_counts->{$type}};
+		foreach $spkr (@spkrs) {
+		    my $gndr = $spkr_info->{$spkr}{GENDER};
+		    foreach $subtype (keys %$subtypes) {
+			my $count = $type_counts->{$type}{$spkr}{$subtype};
+			next unless $count;
+			if ($type eq "CONFUSION") {
+			    foreach $sys_subtype (keys%$count) {
+				$nconf{ALL}{$subtype}{$sys_subtype} += $count->{$sys_subtype};
+				$nconf{ALL}{$subtype}{$sys_subtype} = 0 if not $nconf{ALL}{$subtype}{$sys_subtype};
+				$nconf{ALL}{$sys_subtype}{$subtype} = 0 if not $nconf{ALL}{$sys_subtype}{$subtype};
+			    }
+			    next;
+			}
+			$nconf{ALL}{$subtype}{"{Miss}"} += $count if $type eq "DEL";
+			$nconf{ALL}{"{FA}"}{$subtype} += $count if $type eq "INS";
+			$nconf{ALL}{$subtype}{"{Miss}"} = 0 unless defined $nconf{ALL}{$subtype}{"{Miss}"};
+			$nconf{ALL}{"{FA}"}{$subtype} = 0 unless defined $nconf{ALL}{"{FA}"}{$subtype};
+			$nevent{ALL}{$type} += $count;
+			$nevent{"c=$chnl f=$file"}{$type} += $count if $opt_a =~ /c/i and $opt_a =~ /f/i;
+			$nevent{"c=$chnl"}{$type} += $count if $opt_a =~ /c/i and not $opt_a =~ /f/i;
+			$nevent{"f=$file"}{$type} += $count if $opt_a =~ /f/i and not $opt_a =~ /c/i;
+			$nevent{"s=$spkr"}{$type} += $count if $opt_a =~ /s/i;
+			$nevent{"g=$gndr"}{$type} += $count if $opt_a =~ /g/i;
+		    }
+		}
+	    }
+	}
+    }
+    print_md_scores ($metadata_type, \%nevent, \%nconf, \%offsets, \%nwerr);
+}
+
+#################################
+
+sub print_offset_stats {
+
+    my ($counts) = @_;
+    my (@offsets, $count, $min, $max, $i);
+
+    @offsets = (keys %{$counts->{WBEG}}, keys %{$counts->{WEND}});
+    $min = min (-3, @offsets);
+    $max = max (3, @offsets);
+    print "  word offsets:  <-3  ";
+    for ($i=-3; $i<=3; $i++) {
+	printf "%5d", $i;
+    }
+    print "     >3\n";
+    print "           BEG:";
+    for ($count=0,$i=$min; $i<-3; $i++) {
+	$count += $counts->{WBEG}{$i} if defined $counts->{WBEG}{$i};
+    }
+    printf "%5d  ", $count if defined $count;
+    print "    -  ", unless defined $count;
+    for ($i=-3; $i<=3; $i++) {
+	$count = $counts->{WBEG}{$i};
+	printf "%5d", $count if defined $count;
+	print "    -", unless defined $count;
+    }
+    for ($count=0,$i=4; $i<=$max; $i++) {
+	$count += $counts->{WBEG}{$i} if defined $counts->{WBEG}{$i};
+    }
+    printf "%7d", $count if defined $count;
+    print "      -", unless defined $count;
+
+    print "\n           END:";
+    for ($count=0,$i=$min; $i<-3; $i++) {
+	$count += $counts->{WEND}{$i} if defined $counts->{WEND}{$i};
+    }
+    printf "%5d  ", $count if defined $count;
+    print "    -  ", unless defined $count;
+    for ($i=-3; $i<=3; $i++) {
+	$count = $counts->{WEND}{$i};
+	printf "%5d", $count if defined $count;
+	print "    -", unless defined $count;
+    }
+    for ($count=0,$i=4; $i<=$max; $i++) {
+	$count += $counts->{WEND}{$i} if defined $counts->{WEND}{$i};
+    }
+    printf "%7d", $count if defined $count;
+    print "      -", unless defined $count;
+    print "\n";
+}
+
+#################################
+
+sub print_md_scores {
+
+    my ($metadata_type, $event_counts, $conf_counts, $offset_counts, $word_counts) = @_;
+    my ($type, $nerr, $norm, $name, $ref, $sys, $category, $counts);
+    my ($count, $min, $max, $i, @offsets);
+    my $head_format = "%36s   %5s %5s %5s   %6s %6s %6s   %6s %6s\n";
+    my $data_format = "%-28.28s   %5d   %5d %5d %5s   %6.2f %6.2f %6.2f   %6.2f %6.2f\n";
+    my @header = ("Nref", "Ndel", "Nins", "Nsub", "%Del", "%Ins", "%Sub", "%D+I", "%Tot");
+
+    $counts = $word_counts->{ALL};
+    $nerr = $counts->{DEL} + $counts->{INS};
+    $nerr += $counts->{SUB} if $metadata_type =~ /^(SU|FILLER)$/;
+    printf "\n*** Performance analysis for %ss ***  overall error SCORE = %.2f%s\n",
+        $metadata_type,	100*$nerr/max($counts->{REF},$epsilon), "%";
+
+#metadata word detection
+    print "\nSU (exact) end detection statistics" if $metadata_type eq "SU";
+    print "\nIP (exact) detection statistics" if $metadata_type eq "IP";
+    print "\n$metadata_type word coverage statistics" unless $metadata_type =~ /^(SU|IP)$/;
+    print " -- in terms of reference words\n";
+    printf $head_format, @header;
+    foreach $category (sort keys %$word_counts) {
+	printf $data_format, ($category ne "ALL" ? $category : " "x17 ."ALL",
+			      error_output ($word_counts->{$category}));
+    }
+
+#metadata event detection
+    print "\n$metadata_type detection statistics -- in terms of \# of $metadata_type"."s\n";
+    printf $head_format, @header;
+    foreach $category (sort keys %$event_counts) {
+	printf $data_format, ($category ne "ALL" ? $category : " "x17 ."ALL",
+			      error_output ($event_counts->{$category}));
+    }
+
+#metadata event classification
+    print "\n$metadata_type detection confusion matrix -- in terms of \# of $metadata_type"."s\n";
+    foreach $category (sort keys %$conf_counts) {
+	$counts = $conf_counts->{$category};
+	printf "%24.24s", "$category - ref\\sys";
+	foreach $name (sort keys %$counts, "{Miss}") {
+	    next if $name eq "{FA}";
+	    print "    " if $name eq "{Miss}";
+	    printf "%10.8s", $name;
+	}
+	print "\n";
+	foreach $ref (sort keys %$counts) {
+	    print "\n" if $ref eq "{FA}";
+	    printf "%24.24s", $ref;
+	    foreach $sys (sort keys %$counts, "{Miss}") {
+		next if $sys eq "{FA}" or ($ref eq "{FA}" and $sys eq "{Miss}");
+		print "    " if $sys eq "{Miss}";
+		printf "%8d  ", $counts->{$ref}{$sys} ? $counts->{$ref}{$sys} : 0;
+	    }
+	    print "\n";
+	}
+    }
+
+#offsets
+    foreach $category (sort keys %$offset_counts) {
+	print "\n$metadata_type word offset statistics for $category data\n";
+	print_offset_stats ($offset_counts->{$category});
+    }
+}
+
+#################################
+
+sub error_output {
+
+    my ($counts) = @_;
+    my (@output, $item, $nerr);
+
+    foreach $item ("REF", "DEL", "INS", "SUB") {
+	$counts->{$item} = 0 unless defined $counts->{$item};
+	push @output, $counts->{$item};
+	$nerr += $counts->{$item} unless $item eq "REF";
+    }
+
+    my $norm = 100/max($counts->{REF},$epsilon);
+    foreach my $item ("DEL", "INS", "SUB") {
+	push @output, min(999.99,$norm*$counts->{$item});
+    }
+    my $dpi = $counts->{"DEL"}+$counts->{"INS"};
+    my $tot = $dpi+$counts->{"SUB"};
+    push @output, min(999.99,$norm*$dpi), min(999.99,$norm*$tot);
+    return @output;
+}
+
+#################################
+
+sub word_kinds {
+
+    my ($words, $kind) = @_;
+    my ($word, %count);
+
+    foreach $word (@$words) {
+	$count{$word->{$kind}}++;
+    }
+    return sort keys %count;
+}
+
+#################################
+
+sub standardize_word {
+
+    my ($word, $glm) = @_;
+    my (@split_word, @words, $tbeg, $tdur, $part, $new_word);
+
+    $word->{WORD} =~ lc $word->{WORD}; #lower case
+
+    if (defined $glm->{$word->{WORD}}) { #split glm words
+	@split_word = @{$glm->{$word->{WORD}}};
+    }
+    elsif ($word->{WORD} =~ /^([^-]+|mm-hmm|uh-huh|um-hmm)$/) {
+	return $word;
+    }
+    elsif ($word->{WORD} =~ /.+-.+/) { #split hyphenated words
+	$word->{WORD} =~ s/(.+)-(.+)/$1 $2/g;
+	@split_word = split /\s+/, $word->{WORD};
+    }
+    else { #don't split word
+	return $word;
+    }
+
+#split word and prorate time equally to each part
+    $tbeg = $word->{TBEG};
+    $tdur = $word->{TDUR}/@split_word;
+    foreach $part (@split_word) {
+	$new_word = {FILE => $word->{FILE}, CHNL => $word->{CHNL}, TBEG => $tbeg,
+		     TDUR => $tdur, TEND => $tbeg+$tdur, TMID => $tbeg+$tdur/2,
+		     WORD => $part, CONF => $word->{CONF}, SPKR => $word->{SPKR},
+		     TYPE => $word->{TYPE}, SUBT => $word->{SUBT}, WTYP => $word->{WTYP}};
+	push @words, $new_word;
+	$tbeg += $tdur;
+    }
+    return @words;
+}
+
+#################################
+
+sub decide_who_spoke_the_words {
+
+    my ($ref_wds, $sys_wds) = @_;
+    my ($ref_index, $ref_word, $sys_index, $index, $word, $md_index, $md);
+    my ($sys_word, $spkr, $score, $best_spkr, $best_score, @speakers);
+
+#select the best ref word for each STT output word that has multiple reference word matches
+    for ($sys_index=0; $sys_index<@$sys_wds; $sys_index++) {
+	$sys_word = $sys_wds->[$sys_index];
+	next unless defined $sys_word->{SPKRS};
+	undef $best_score;
+	@speakers = sort keys %{$sys_word->{SPKRS}};
+	next unless @speakers > 1;
+	foreach $spkr (@speakers) {
+	    next unless defined $sys_word->{SPKRS}{$spkr};
+	    $ref_word = $sys_word->{SPKRS}{$spkr}{REFPTR};
+	    $score = $ref_word->{PATHS}{$sys_index}{SCORE};
+	    next if defined $best_score and $best_score > $score;
+	    $best_score = $score;
+	    $best_spkr = $spkr;
+	}
+	next unless defined $best_score;
+	foreach $spkr (@speakers) {
+	    next if $spkr eq $best_spkr;
+	    $sys_word->{SPKRS}{$spkr} = undef;
+	    $ref_word = $sys_word->{SPKRS}{$best_spkr}{REFPTR};
+	}
+    }
+}
+
+#################################
+
+sub event_covers_time {
+
+    my ($event, $time) = @_;
+
+    return ($time < $event->{TBEG} or
+	    $time > $event->{TEND}) ? 0 : 1;
+}
+
+#################################
+
+sub word_score {
+
+    my ($ref_word, $sys_word) = @_;
+    my ($tbeg, $tend, $rw, $sw, $score, $word);
+    my ($attribute, $attributes, $ref_attributes, $sys_attributes);
+
+#compute joint word coverage
+    $score = 0;
+    if (defined $ref_word and defined $sys_word) {
+	return undef unless overlap ($ref_word, $sys_word, $word_gap);
+	if (($ref_attributes = $ref_word->{ATTRIBUTES}) and
+	    ($sys_attributes = $sys_word->{ATTRIBUTES})) {
+	    foreach $attribute ("EDIT", "FILLER", "IP", "SU") {
+	        next unless (defined $ref_attributes->{$attribute} and
+			     defined $sys_attributes->{$attribute});
+		$score += ($ref_attributes->{$attribute} eq
+			   $sys_attributes->{$attribute}) ? 0.02 : 0.01;
+	    }
+	}
+	return $score if #both word type and word spelling match
+	    ((   $ref_word->{WORD} eq $sys_word->{WORD} and
+		 $ref_word->{WTYP} eq $sys_word->{WTYP})
+
+	     or ($ref_word->{WTYP} eq "lex" and
+		 $sys_word->{WTYP} eq "frag" and
+		 ($sw = $sys_word->{WORD}, $sw =~ s/^-*|-*$//g, $sw) #make sure that $sw is non-null
+		 and ($ref_word->{WORD} =~ /$sw/))
+
+	     or ($ref_word->{WTYP} eq "frag" and
+		 $sys_word->{WTYP} eq "lex" and
+		 ($rw = $ref_word->{WORD}, $rw =~ s/^-*|-*$//g, $rw) #make sure that $rw is non-null
+		 and ($sys_word->{WORD} =~ /$rw/))
+
+	     or ($ref_word->{WTYP} eq "fp" and
+		 $sys_word->{WTYP} eq "fp")
+
+	     or ($ref_word->{WTYP} eq "frag" and
+		 $sys_word->{WTYP} eq "frag"));
+
+	return $score - 0.1*max(1,ref_count($ref_word)) if #word type match, except for lex's
+	    ((   $ref_word->{WTYP} eq $sys_word->{WTYP} and
+		 $ref_word->{WTYP} ne "lex"));
+
+	return $score - max(1,ref_count($ref_word),ref_count($sys_word));
+    }
+    $word = defined $ref_word ? $ref_word : $sys_word;
+    return 0 unless defined $word;
+    $score = $word->{WTYP} eq "lex" ? -ref_count($word) : -0.2*max(1,ref_count($word));
+    $attributes = $word->{ATTRIBUTES};
+    if (defined $attributes) {
+	foreach $attribute ("EDIT", "FILLER", "IP", "SU") {
+	    $score += 0.005 if defined $word->{$attribute};
+	}
+    }
+    return $score;
+}
+
+#################################
+
+sub wd_err_count {
+
+    my ($ref_word, $sys_word) = @_;
+
+    my $word_score = word_score($ref_word,$sys_word);
+    return (defined $word_score and $word_score > -0.5) ? 0 : 1;
+}
+
+#################################
+
+sub ref_count {
+
+    my ($word) = @_;
+
+    return 0 unless defined $word;
+    return 0 if $word->{WTYP} =~ /^(non-lex|misc)$/;
+
+#hyphenated words get a count of 2 (except for mm-hmm, uh-huh and hm-hmm)
+    my $WORD = $word->{WORD};
+    $WORD =~ s/^-*|-*$//g;
+    return $WORD =~ /^([^-]+|mm-hmm|uh-huh|um-hmm)$/ ? 1 : 2;
+}
+
+#################################
+
+sub overlap {
+
+    my ($ref, $sys, $tgap) = @_;
+
+    return 0 unless $ref and $sys;
+    $tgap = 0 unless defined $tgap;
+    my $tovl = (min($ref->{TEND}, $sys->{TEND}) -
+		max($ref->{TBEG}, $sys->{TBEG})) + $tgap;
+    return $tovl > 0 ? $tovl/(1 + $tgap/max($ref->{TDUR},$epsilon)) : 0;
+}
+
+################################
+
+sub md_in_uem {
+
+    my ($md, $uem_eval) = @_;
+
+    return 1 unless defined $uem_eval; #not using UEM partition specification
+    foreach my $partition (@$uem_eval) {
+        return 1 if ($md->{TEND} <= $partition->{TEND}+$epsilon and
+		     $md->{TBEG} >= $partition->{TBEG}-$epsilon);
+    }
+    return 0;
+}
+
+#################################
+
+sub map_spkrdata_to_words {
+
+    my ($sys_mds, $sys_wds, $ref_mds, $ref_wds) = @_;
+    my ($spkr, $md, @ref_spkr_mds, @sys_spkr_mds);
+
+    foreach $spkr (keys %$ref_mds) {
+	foreach $md (@{$ref_mds->{$spkr}}) {
+	    push @ref_spkr_mds, $md;
+	}
+    }
+
+    foreach $spkr (keys %$sys_mds) {
+	foreach $md (@{$sys_mds->{$spkr}}) {
+	    push @sys_spkr_mds, $md;
+	}
+    }
+
+    map_metadata_to_words (\@sys_spkr_mds, $sys_wds, \@ref_spkr_mds, $ref_wds);
+}
+
+#################################
+
+sub map_metadata_to_words {
+
+    my ($sys_mds, $sys_wds, $ref_mds, $ref_wds) = @_;
+
+#map system output metadata times to ref words
+    foreach my $md (@$sys_mds) {
+	if ($opt_w) { #adjust times/words to agree with ref-sys word alignment
+	    $md->{RTBEG} = adjust_sys_time_to_ref ($md->{TBEG}, $sys_wds);
+	    $md->{RTEND} = adjust_sys_time_to_ref ($md->{TEND}, $sys_wds);
+	}
+	else { #map system output metadata event to reference data normally
+	    $md->{RTBEG} = $md->{TBEG};
+	    $md->{RTEND} = $md->{TEND};
+	}
+	$md->{RTDUR} = $md->{RTEND} - $md->{RTBEG};
+	$md->{RTMID} = $md->{RTBEG} + $md->{RTDUR}/2;
+	($md->{RWBEG}, $md->{RWEND}) = md_ref_word_indices ($md, $ref_wds);
+	$md->{RWDUR} = $md->{RWEND} - $md->{RWBEG} + 1;
+    }
+
+#map reference metadata times to ref words
+    foreach my $md (@$ref_mds) {
+	($md->{WBEG}, $md->{WEND}) = md_word_indices ($md, $ref_wds);
+	$md->{WDUR} = $md->{WEND} - $md->{WBEG} + 1;
+	next if ($md->{WDUR} > 0 or
+		 $md->{TYPE} =~ /^(IP|CB)$/);
+        next if (not $opt_W and not $opt_w and $md->{TYPE} eq "SPEAKER");
+	warn "\nWARNING:  reference metadata event subsumes no reference words\n"
+	    ."    file='$md->{FILE}', chnl='$md->{CHNL}', tbeg='$md->{TBEG}',"
+		." tend='$md->{TEND}', type='$md->{TYPE}', subtype='$md->{SUBT}'\n";
+    }
+
+#friendly (unused) check of system metadata times versus sys words
+    return unless $opt_w;
+    foreach my $md (@$sys_mds) {
+	(my $wbeg, my $wend) = md_word_indices ($md, $sys_wds);
+	next if ($wend - $wbeg >= 0 or
+		 $md->{TYPE} =~ /^(IP|CB)$/);
+	warn "\nWARNING:  system output metadata event subsumes no system output words\n"
+	    ."    file='$md->{FILE}', chnl='$md->{CHNL}', tbeg='$md->{TBEG}',"
+		." tend='$md->{TEND}', type='$md->{TYPE}', subtype='$md->{SUBT}'\n";
+    }
+}
+
+#################################
+
+sub adjust_sys_time_to_ref {
+
+    my ($ts, $sys_wds) = @_;
+    my ($ts1, $ts2, $tr, $tr1, $tr2, $ws1, $ws2, $ref_wd);
+
+#given a time in the system output, find the time in the reference
+#that harmonizes with the alignment of system output words
+
+#find the nearest right reference anchor point
+    $ws2 = 0;
+    $ws2++ while ($ws2 < @$sys_wds and
+		  ($sys_wds->[$ws2]{TEND} < $ts or
+		   not defined $sys_wds->[$ws2]{MAPPTR}));
+    if ($ws2 < @$sys_wds) {
+	$ref_wd = $sys_wds->[$ws2]{MAPPTR};
+	($ts2, $tr2) = $sys_wds->[$ws2]{TBEG} < $ts ?
+	    ($sys_wds->[$ws2]{TEND}, $ref_wd->{TEND}) :
+	    ($sys_wds->[$ws2]{TBEG}, $ref_wd->{TBEG});
+    }
+
+#find the nearest left reference anchor point
+    $ws1 = min($ws2, @$sys_wds-1);
+    $ws1-- while ($ws1 >= 0 and
+		  ($sys_wds->[$ws1]{TBEG} > $ts or
+		   not defined $sys_wds->[$ws1]{MAPPTR}));
+    if ($ws1 >= 0) {
+	$ref_wd = $sys_wds->[$ws1]{MAPPTR};
+	($ts1, $tr1) = $sys_wds->[$ws1]{TEND} > $ts ?
+	    ($sys_wds->[$ws1]{TBEG}, $ref_wd->{TBEG}) :
+	    ($sys_wds->[$ws1]{TEND}, $ref_wd->{TEND});
+    }
+
+#make adjustment
+    $tr = (($ws1 < 0 and $ws2 >= @$sys_wds) ? $ts               : #no adjustment possible
+	   ($ws1 < 0)                       ? $tr2 + ($ts-$ts2) : #extrapolate left without scale change
+	   ($ws2 >= @$sys_wds)              ? $tr1 + ($ts-$ts1) : #extrapolate right without scale change
+	   ($ts == $ts1)                    ? $tr1              : #no interpolation necessary
+	   $tr1 + ($ts-$ts1)*($tr2-$tr1)/($ts2-$ts1));            #normal interpolation
+    return $tr;
+}
+
+#################################
+
+sub md_word_indices {
+
+    my ($md, $wds) = @_;
+
+#find the word indices of the first and last words with midpoints inside the metadata event
+    my $i = 0;
+    $i++ while ($i<@$wds and ($wds->[$i]{TMID}) < $md->{TBEG});
+    my $j = max($i-1,0);
+    $j++ while ($j<@$wds and ($wds->[$j]{TMID}) <= $md->{TEND});
+    return ($i, --$j);
+}
+
+#################################
+
+sub md_ref_word_indices {
+
+    my ($md, $wds) = @_;
+
+#find the word indices of the first and last words with midpoints inside the metadata event
+    my $i = 0;
+    $i++ while ($i<@$wds and ($wds->[$i]{TMID}) < $md->{RTBEG});
+    my $j = max($i-1,0);
+    $j++ while ($j<@$wds and ($wds->[$j]{TMID}) <= $md->{RTEND});
+    return ($i, --$j);
+}
+
+#################################
+
+sub align_data {
+
+    my ($refs, $syss, $spkr, $scorer, $max_delta_score) = @_;
+    my ($ref, $sys, $prev_ref, $path, $ref_path);
+    my ($ref_index, $sys_index, $index, $pruning_threshold);
+    my ($score, $path_score, $best_score, %cum_insertion_score);
+
+#compute cumulative insertion score for sys output
+    $cum_insertion_score{-1} = 0;
+    for ($sys_index=0; $sys_index<@$syss; $sys_index++) {
+	$sys = $syss->[$sys_index];
+	$cum_insertion_score{$sys_index} = $cum_insertion_score{$sys_index-1};
+	$cum_insertion_score{$sys_index} += &$scorer (undef, $sys);
+    }
+
+#find the best path by incremental optimization through the ref transcription
+    $prev_ref->{PATHS}{-1}{SCORE} = 0;
+    for ($ref_index=0; $ref_index<@$refs; $ref_index++) {
+	$ref = $refs->[$ref_index];
+	next if $spkr and $ref->{SPKR} ne $spkr;
+
+#find best score and compute pruning threshold
+	$best_score = undef;
+	foreach $index (keys %{$prev_ref->{PATHS}}) {
+	    $path_score = $prev_ref->{PATHS}{$index}{SCORE} +
+		$cum_insertion_score{@$syss-1}-$cum_insertion_score{$index};
+	    $best_score = $path_score if not defined $best_score or $best_score < $path_score;
+	}
+	$pruning_threshold = $best_score - $max_delta_score;
+
+#extend paths with scores above pruning threshold
+	foreach $index (keys %{$prev_ref->{PATHS}}) {
+	    $path_score = $prev_ref->{PATHS}{$index}{SCORE} +
+		$cum_insertion_score{@$syss-1}-$cum_insertion_score{$index};
+	    next unless $path_score > $pruning_threshold;
+	    $ref->{PATHS}{$index}{PATHPTR} = $index;
+	    $ref->{PATHS}{$index}{PREVREF} = $prev_ref;
+	    $ref->{PATHS}{$index}{SCORE} = $prev_ref->{PATHS}{$index}{SCORE} +
+		&$scorer ($ref, undef);
+	}
+
+#compare the current ref event to all sys events
+	for ($sys_index=0; $sys_index<@$syss; $sys_index++) {
+	    $sys = $syss->[$sys_index];
+	    $score = &$scorer ($ref, $sys);
+	    next unless defined $score;
+
+#update each path for this {ref, sys} match
+	    foreach $index (sort {$a<=>$b} keys %{$prev_ref->{PATHS}}) {
+		next unless $index < $sys_index;
+		$path_score = $score + $prev_ref->{PATHS}{$index}{SCORE} +
+		    $cum_insertion_score{$sys_index-1}-$cum_insertion_score{$index};
+		if (not defined $ref->{PATHS}{$sys_index}
+		    or $path_score > $ref->{PATHS}{$sys_index}{SCORE}) {
+		    $ref->{PATHS}{$sys_index}{SCORE} = $path_score;
+		    $ref->{PATHS}{$sys_index}{PREVREF} = $prev_ref;
+		    $ref->{PATHS}{$sys_index}{PATHPTR} = $index;
+		    $ref->{PATHS}{$sys_index}{SYSPTR} = $sys;
+		}
+	    }
+	}
+	$prev_ref=$ref;
+    }
+
+#add insertion score for remaining unmapped sys events
+    foreach $index (sort {$a<=>$b} keys %{$prev_ref->{PATHS}}) {
+	$prev_ref->{PATHS}{$index}{SCORE} +=
+	    $cum_insertion_score{@$syss-1}-$cum_insertion_score{$index} if $index < @$syss-1;
+    }
+}
+
+#################################
+
+sub md_score {
+
+    my ($ref_md, $sys_md) = @_;
+    my ($beg, $end, $overlap, $ref_beg, $sys_beg, $md_dur);
+    my $subtype_bonus = 1.1; #multiplicative bonus for matching subtypes
+    my $endword_bonus = 1.001; #multiplicative bonus for matching boundaries
+
+    return 0 unless defined $ref_md and defined $sys_md;
+
+    if ($opt_W) { #compute md mapping score as ref-sys overlap in (ref) words
+	$ref_beg = $ref_md->{WBEG};
+	$sys_beg = $sys_md->{RWBEG};
+	if ($ref_md->{TYPE} eq "SU") {
+	    $ref_beg = max($ref_beg, $ref_md->{WEND}-($su_extent_limit-1));
+	    $sys_beg = max($sys_beg, $sys_md->{RWEND}-($su_extent_limit-1));
+	}
+	$beg = max($ref_beg, $sys_beg);
+	$end = min($ref_md->{WEND}, $sys_md->{RWEND});
+	$overlap = $end - $beg + 1;
+	$md_dur = $ref_md->{WEND} - $ref_beg + 1;
+    }
+    else { #compute md mapping score as ref-sys overlap in time
+	$ref_beg = $ref_md->{TBEG};
+	$sys_beg = $sys_md->{RTBEG};
+	if ($ref_md->{TYPE} eq "SU") {
+	    $ref_beg = max($ref_beg, $ref_md->{TEND}-$su_extent_limit);
+	    $sys_beg = max($sys_beg, $sys_md->{RTEND}-$su_extent_limit);
+	}
+	$beg = max($ref_beg, $sys_beg);
+	$end = min($ref_md->{TEND}, $sys_md->{RTEND});
+	$overlap = $end - $beg;
+	$md_dur = $ref_md->{TEND} - $ref_beg;
+    }
+    $overlap += $epsilon if $ref_md->{TYPE} =~ /^(IP|CB)$/;
+    $overlap += $md_gap;
+    return undef if $overlap < 0;
+    $overlap *= $subtype_bonus if $ref_md->{SUBT} eq $sys_md->{SUBT};
+    $overlap *= $endword_bonus if $ref_md->{WEND} eq $sys_md->{RWEND};
+    return $overlap if $md_dur+$md_gap < max($md_dur,$epsilon);
+    return $overlap * max($md_dur,$epsilon)/($md_dur+$md_gap);
+}
+
+#################################
+
+sub trace_best_path {
+
+    my ($refs, $syss, $spkr) = @_;
+    my ($ref, $path, $pathptr, $best_score, $prev_ref, $ref_index, $index, $sys);
+
+#find the last word for the selected channel and speaker
+    return unless @$refs and @$syss;
+    $ref_index = @$refs-1;
+    $ref_index-- while (defined $spkr and $refs->[$ref_index]{SPKR} ne $spkr);
+    $spkr = "ALL" unless defined $spkr;
+
+#identify the best path for the selected ending word
+    $ref = $refs->[$ref_index];
+    undef $best_score;
+    foreach $index (sort {$a<=>$b} keys %{$ref->{PATHS}}) {
+	$path = $ref->{PATHS}{$index};
+	if (not defined $best_score or $path->{SCORE} > $best_score) {
+	    $best_score = $path->{SCORE};
+	    $pathptr = $path->{PATHPTR};
+	    $prev_ref = $path->{PREVREF};
+	    $sys = $path->{SYSPTR};
+	}
+    }
+    if (defined $sys) {
+	$sys->{SPKRS}{$spkr}{REFPTR} = $ref;
+	$sys->{MAPPTR} = $ref;
+	$ref->{MAPPTR} = $sys;
+    }
+
+#trace the path back
+    while ($pathptr != -1) {
+	$ref = $prev_ref;
+	$path = $ref->{PATHS}{$pathptr};
+	$pathptr = $path->{PATHPTR};
+	$prev_ref = $path->{PREVREF};
+	next unless defined $path->{SYSPTR};
+	$sys = $path->{SYSPTR};
+	$sys->{SPKRS}{$spkr}{REFPTR} = $ref;
+	$sys->{MAPPTR} = $ref;
+	$ref->{MAPPTR} = $sys;
+    }
+}
+
+#################################
+
+sub delta_metadata_error_words {
+
+#accumulates the number of metadata error words difference
+#between ref beg/end point of metadata event and sys beg/end point of metadata event
+
+    my ($location, $ref_index, $sys_index, $ref_wds) = @_;
+
+    my $dw = 0;
+    my $index = min($ref_index,$sys_index);
+    my $istop = max($ref_index,$sys_index);
+    while ($index != $istop) {
+	$index++ if $location eq "END";
+	$dw++ if $index >= 0 and $index < @$ref_wds and $ref_wds->[$index]{SCOREABLE};
+	$index++ if $location eq "BEG";
+    }
+    return $sys_index > $ref_index ? $dw : 0-$dw;
+}
+
+#################################
+
+sub print_path_score {
+
+    my ($ref, $sys, $ref_count, $err_count, $err_type) = @_;
+
+#print header
+    unless (defined $ref or defined $sys) {
+	printf " ref del ins sub %16.16s %-7s%8s%8s %-12.12s", "REF:  token", "type",
+	    "tbeg", "tend", "speaker";
+	printf " %16.16s %-7s  %7s%8s %8s%8s %-12.12s\n", "SYS:  token", "type",
+	    "Rtbeg", "Rtend", "tbeg", "tend", "sys-speaker" if $opt_w;
+	printf " %16.16s %-7s%8s%8s %-12.12s\n", "SYS:  token", "type",
+	    "tbeg", "tend", "speaker" unless $opt_w;
+	return;
+    }
+
+#print ref
+    my %errors = (REF=>"-", DEL=>"-", INS=>"-", SUB=>"-");
+    $errors{REF} = $ref_count if defined $ref_count;
+    $errors{$err_type} = $err_count if defined $err_type;
+    printf "%4s%4s%4s%4s", $errors{REF}, $errors{DEL}, $errors{INS}, $errors{SUB};
+
+    if (defined $ref) {
+	printf " %16.16s %-7s%8.2f%8.2f %-12.12s", $ref->{TYPE} =~ /^(LEXEME|NON-LEX|NON-SPEECH)$/ ?
+	    ($ref->{WORD}, $ref->{WTYP}) : ($ref->{SUBT}, $ref->{TYPE}), $ref->{TBEG}, $ref->{TEND}, $ref->{SPKR};
+    }
+    else {
+	printf " %16.16s %-7s%8s%8s %-12.12s", "---", "---", "--- ", "--- ", "---";
+    }
+
+#print sys
+    if ($opt_w) {
+	if (defined $sys) {
+	    printf " %16.16s %-7s (%7.2f%8.2f)%8.2f%8.2f %-12.12s\n", $sys->{TYPE} =~ /^(LEXEME|NON-LEX|NON-SPEECH)$/ ?
+		($sys->{WORD}, $sys->{WTYP}) : ($sys->{SUBT}, $sys->{TYPE}), $sys->{RTBEG}, $sys->{RTEND}, $sys->{TBEG}, $sys->{TEND}, $sys->{SPKR};
+	}
+	else {
+	    printf " %16.16s %-7s (%7s%8s)%8s%8s %-12.12s\n", "---", "---", "--- ", "--- ", "--- ", "--- ", "---";
+	}
+    }
+    else {
+	if (defined $sys) {
+	    printf " %16.16s %-7s%8.2f%8.2f %-12.12s\n", $sys->{TYPE} =~ /^(LEXEME|NON-LEX|NON-SPEECH)$/ ?
+		($sys->{WORD}, $sys->{WTYP}) : ($sys->{SUBT}, $sys->{TYPE}), $sys->{TBEG}, $sys->{TEND}, $sys->{SPKR};
+	}
+	else {
+	    printf " %16.16s %-7s%8s%8s %-12.12s\n", "---", "---", "--- ", "--- ", "---";
+	}
+    }
+}
+
+#################################
+
+sub score_metadata_path {
+
+    my ($type, $file, $chnl, $ref_mds, $sys_mds, $ref_wds) = @_;
+    my ($ref_md, @sys_mds, $sys_index, $sys_md, $md, $spkr, $iw);
+    my (%count, $ref_count, $err_count, $ref_wd, $dw);
+
+    print "\n$type alignment and scoring details for channel $chnl of file $file\n" if $opt_D;
+    print_path_score () if $opt_D;
+
+#tabulate boundary/depod errors
+    tag_ref_words_with_metadata_info ($ref_mds, $ref_wds, "REF");
+    tag_ref_words_with_metadata_info ($sys_mds, $ref_wds, "SYS");
+    for ($iw=0; $iw<@$ref_wds; $iw++) {
+	$ref_wd = $ref_wds->[$iw];
+	next unless $ref_wd->{SCOREABLE} or $type =~ /^(IP|SU)$/;
+	my $nref = my $nsys = my $nins = my $ncor = 0;
+	foreach my $subtype (keys %{$md_subtypes{$type}}) {
+	    my $nr = $ref_wd->{"REF-$type"}{$subtype}{MAP};
+	    my $nm = $ref_wd->{"REF-$type"}{$subtype}{NOT};
+	    my $ns = $ref_wd->{"SYS-$type"}{$subtype}{MAP};
+	    my $ni = $ref_wd->{"SYS-$type"}{$subtype}{NOT};
+	    $nref += $nr if $nr;
+	    $nref += $nm if $nm;
+	    $nsys += $ns if $ns;
+	    $nins += $ni if $ni;
+	    $ncor += min($nr,$ns) if $nr and $ns;
+	}
+	$count{WORDS}{REF} += $nref;
+	$count{WORDS}{DEL} += max($nref-$nsys,0);
+	$count{WORDS}{INS} += max($nsys-$nref,0) + ($nins ? $nins : 0);
+	$count{WORDS}{SUB} += min($nref,$nsys) - $ncor;
+    }
+
+#tabulate beg/end word offset errors
+    foreach $ref_md (@$ref_mds) {
+	next unless ($sys_md = $ref_md->{MAPPTR});
+	$dw = delta_metadata_error_words ("BEG", $ref_md->{WBEG}, $sys_md->{RWBEG}, $ref_wds);
+	$count{WORD_OFFSET}{WBEG}{$dw}++;
+	$dw = delta_metadata_error_words ("END", $ref_md->{WEND}, $sys_md->{RWEND}, $ref_wds);
+	$count{WORD_OFFSET}{WEND}{$dw}++;
+    }
+
+#tabulate detection errors
+    @sys_mds = @$sys_mds;
+    $sys_md = shift @sys_mds;
+    foreach $ref_md (@$ref_mds) {
+	$spkr = $ref_md->{SPKR};
+	$ref_count = md_err_count ($ref_md, undef);
+	$count{REF}{$spkr}{$ref_md->{SUBT}} += $ref_count if defined $ref_count;
+	if ($ref_md->{MAPPTR}) {
+	    while ($sys_md and
+		   $sys_md ne $ref_md->{MAPPTR}) {
+		printf "%sUNEXPECTED MAPPED SYS MD:  %16s %-7s%8.2f%8.2f %-16s\n",
+		    " "x44, $sys_md->{SUBT}, $sys_md->{TYPE}, $sys_md->{TBEG},
+		    $sys_md->{TEND}, $sys_md->{SPKR} if $sys_md->{MAPPTR};
+		$err_count = md_err_count (undef, $sys_md);
+		$count{INS}{ref_spkr_of_md($sys_md,$ref_wds)}{$sys_md->{SUBT}} += $err_count;
+		print_path_score (undef, $sys_md, 0, $err_count, "INS") if $opt_D;
+		$sys_md = shift @sys_mds;
+	    }
+	    if ($sys_md) {
+		$err_count = md_err_count ($ref_md, $sys_md);
+		$count{SUB}{$spkr}{$ref_md->{SUBT}} += $err_count;
+		$count{CONFUSION}{$spkr}{$ref_md->{SUBT}}{$sys_md->{SUBT}} += $ref_count;
+		print_path_score ($ref_md, $sys_md, $ref_count, $err_count, "SUB") if $opt_D;
+		$sys_md = shift @sys_mds;
+	    }
+	    else {
+		printf "%sSYS MD NOT FOUND FOR REF MD:   %16s %-7s%8.2f%8.2f %-16s\n",
+		    " "x40, $ref_md->{SUBT}, $ref_md->{TYPE}, $ref_md->{TBEG},
+		    $ref_md->{TEND}, $ref_md->{SPKR} if $ref_md->{MAPPTR};
+	    }
+	}
+	else {
+	    $err_count = md_err_count ($ref_md, undef);
+	    $count{DEL}{$spkr}{$ref_md->{SUBT}} += $err_count;
+	    print_path_score ($ref_md, undef, $ref_count, $err_count, "DEL") if $opt_D;
+	}
+    }
+    while ($sys_md) {
+	printf "%sUNEXPECTED MAPPED SYS MD:  %16s %-7s%8.2f%8.2f %-16s\n",
+	    " "x44, $sys_md->{SUBT}, $sys_md->{TYPE}, $sys_md->{TBEG},
+	    $sys_md->{TEND}, $sys_md->{SPKR} if $sys_md->{MAPPTR};
+	$err_count = md_err_count (undef, $sys_md);
+	$count{INS}{ref_spkr_of_md($sys_md,$ref_wds)}{$sys_md->{SUBT}} += $err_count;
+	print_path_score (undef, $sys_md, 0, $err_count, "INS") if $opt_D;
+	$sys_md = shift @sys_mds;
+    }
+    return {%count};
+}
+
+#################################
+
+sub md_err_count {
+
+    my ($ref_md, $sys_md) = @_;
+
+    return 1 if (not defined $sys_md         or not defined $ref_md         or
+		 not defined $sys_md->{TYPE} or not defined $ref_md->{TYPE} or
+		 not defined $sys_md->{SUBT} or not defined $ref_md->{SUBT} or
+		 $sys_md->{TYPE} ne $ref_md->{TYPE} or
+		 $sys_md->{SUBT} ne $ref_md->{SUBT});
+    return 0;
+}
+
+#################################
+
+sub ref_spkr_of_md {
+
+    my ($md, $ref_wds) = @_;
+    my $spkr;
+
+    for (my $index =min($md->{RWBEG},$md->{RWEND});
+	    $index<=max($md->{RWBEG},$md->{RWEND}); $index++) {
+	next unless $index >= 0 and $index < @$ref_wds;
+	$spkr = $ref_wds->[$index]{SPKR} unless $spkr;
+	return "unknown" unless $ref_wds->[$index]{SPKR} eq $spkr;
+    }
+    return defined $spkr ? $spkr : "unknown";
+}
+
+#################################
+
+sub score_word_path {
+
+    my ($file, $chnl, $ref_wds, $sys_wds) = @_;
+    my ($ref_wrd, @sys_wds, $sys_wrd);
+    my ($ref_count, $err_count);
+
+    print "\nWord alignment and scoring details for channel $chnl of file $file\n";
+    print_path_score ();
+
+#tabulate errors
+    @sys_wds = @$sys_wds;
+    $sys_wrd = shift @sys_wds;
+    foreach $ref_wrd (@$ref_wds) {
+	$ref_count = ref_count($ref_wrd);
+	if ($ref_wrd->{MAPPTR}) {
+	    while ($sys_wrd and
+		   $sys_wrd ne $ref_wrd->{MAPPTR}) {
+		printf "%71s%16s %-7s%s%8.2f%8.2f %-16s\n", "UNEXPECTED MAPPED SYS WORD:",
+		    $sys_wrd->{WORD}, $sys_wrd->{WTYP}, " "x18, $sys_wrd->{TBEG},
+		    $sys_wrd->{TDUR}, $sys_wrd->{SPKR} if $sys_wrd->{MAPPTR};
+		$err_count = wd_err_count(undef, $sys_wrd);
+		print_path_score (undef, $sys_wrd, 0, $err_count, "INS");
+		$sys_wrd = shift @sys_wds;
+	    }
+	    if ($sys_wrd) {
+		$err_count = wd_err_count($ref_wrd, $sys_wrd);
+		print_path_score ($ref_wrd, $sys_wrd, $ref_count, $err_count, "SUB");
+		$sys_wrd = shift @sys_wds;
+	    }
+	    else {
+		printf "%71s%16s %-7s%s%8.2f%8.2f %-16s\n", "SYS WRD NOT FOUND FOR REF WRD:",
+		    $ref_wrd->{WORD}, $ref_wrd->{WTYP}, " "x18, $ref_wrd->{TBEG},
+		    $ref_wrd->{TDUR}, $ref_wrd->{SPKR} if $ref_wrd->{MAPPTR};
+	    }
+	}
+	else {
+	    $err_count = wd_err_count($ref_wrd, undef);
+	    print_path_score ($ref_wrd, undef, $ref_count, $err_count, "DEL");
+	}
+    }
+    while ($sys_wrd) {
+	printf "%71s%16s %-7s%8.2f%8.2f %-16s\n", "UNEXPECTED MAPPED SYS WORD:",
+	    $sys_wrd->{WORD}, $sys_wrd->{WTYP}, $sys_wrd->{TBEG},
+	    $sys_wrd->{TDUR}, $sys_wrd->{SPKR} if $sys_wrd->{MAPPTR};
+	$err_count = wd_err_count(undef, $sys_wrd);
+	print_path_score (undef, $sys_wrd, 0, $err_count, "INS");
+	$sys_wrd = shift @sys_wds;
+    }
+}
+
+#################################
+
+sub date_time_stamp {
+
+    my ($sec, $min, $hour, $mday, $mon, $year, $wday, $yday, $isdst) = localtime();
+    my @months = qw(Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec);
+    my ($date, $time);
+
+    $time = sprintf "%2.2d:%2.2d:%2.2d", $hour, $min, $sec;
+    $date = sprintf "%4.4s %3.3s %s", 1900+$year, $months[$mon], $mday;
+    return ($date, $time);
+}
+
+#################################
+
+sub max {
+
+    my ($max, $next);
+
+    return unless defined ($max=pop);
+    while (defined ($next=pop)) {
+	$max = $next if $next > $max;
+    }
+    return $max;
+}
+
+#################################
+
+sub min {
+
+    my ($min, $next);
+
+    return unless defined ($min=pop);
+    while (defined ($next=pop)) {
+	$min = $next if $next < $min;
+    }
+    return $min;
+}
+
+#################################
+
+sub score_speaker_diarization {
+
+    my ($file, $chnl, $ref_spkr_data, $sys_spkr_data, $ref_wds, $uem_eval, $rttm_data) = @_;
+    my ($uem_score, $ref_eval, $sys_eval, $spkr_overlap, $spkr_map);
+    my ($eval_segs, $score_segs, %stats, @ref_wds, $wrd, $ref_spkr, $sys_spkr);
+    my ($nref, $nsys, $nmap, $spkr, $seg, $type, $spkr_info, $noscore_nl);
+
+    $stats{EVAL_WORDS} = $stats{SCORED_WORDS} =	$stats{MISSED_WORDS} = $stats{ERROR_WORDS} = $epsilon;
+    @ref_wds = @$ref_wds;
+    $wrd = shift @ref_wds;
+    foreach $seg (@$uem_eval) {
+	$stats{EVAL_TIME} += $seg->{TEND}-$seg->{TBEG};
+	$wrd = shift @ref_wds while ($wrd and $wrd->{TMID} < $seg->{TBEG});
+	while ($wrd and $wrd->{TMID} <= $seg->{TEND}) {
+	    $stats{EVAL_WORDS}++;
+	    $wrd = shift @ref_wds;
+	}
+    }
+
+    $eval_segs = create_speaker_segs ($uem_eval, $ref_spkr_data, $sys_spkr_data);
+    foreach $seg (@$eval_segs) {
+	foreach $ref_spkr (keys %{$seg->{REF}}) {
+	    $spkr_info->{REF}{$ref_spkr}{TIME} += $seg->{TDUR};
+	    $spkr_info->{REF}{$ref_spkr}{TYPE} = $ref_spkr_data->{$ref_spkr}[0]{SUBT};
+	}
+	foreach $sys_spkr (keys %{$seg->{SYS}}) {
+	    $spkr_info->{SYS}{$sys_spkr}{TIME} += $seg->{TDUR};
+	    $spkr_info->{SYS}{$sys_spkr}{TYPE} = $sys_spkr_data->{$sys_spkr}[0]{SUBT};
+	}
+	next unless keys %{$seg->{REF}} > 0;
+	$stats{EVAL_SPEECH} += $seg->{TDUR};
+	foreach $ref_spkr (keys %{$seg->{REF}}) {
+	    foreach $sys_spkr (keys %{$seg->{SYS}}) {
+		$spkr_overlap->{$ref_spkr}{$sys_spkr} += $seg->{TDUR};
+	    }
+	}
+    }
+    $speaker_map{$file}{$chnl} = $spkr_map = map_speakers ($spkr_overlap)
+	if defined $spkr_overlap;
+    print_speaker_map ($spkr_map, $spkr_overlap) if $opt_m;
+    update_speaker_map_file ($spkr_map, $spkr_overlap, $file, $chnl, $opt_M) if $opt_M;
+
+    $uem_score = $collar > 0 ? add_collars_to_uem ($uem_eval, $ref_spkr_data) : $uem_eval;
+    $uem_score = add_exclusion_zones_to_uem ($noscore_sd, $uem_score, $rttm_data);
+    $noscore_nl->{"NON-LEX"} = $noscore_sd->{"NON-LEX"};
+    $uem_score = add_exclusion_zones_to_uem ($noscore_nl, $uem_score, $rttm_data, $max_extend);
+    $uem_score = exclude_overlapping_speech_from_uem ($uem_score, $rttm_data) if $opt_1;
+    tag_scoreable_words ($ref_wds, $uem_score);
+    $score_segs = create_speaker_segs ($uem_score, $ref_spkr_data, $sys_spkr_data);
+    print_speaker_segs ($score_segs, $file, $chnl) if $opt_v;
+    ($stats{TYPE}{NSPK}) = speaker_mapping_scores ($spkr_map, $spkr_info);
+    score_speaker_segments (\%stats, $score_segs, $ref_wds, $spkr_map, $spkr_info);
+    return {%stats};
+}
+
+#################################
+
+sub speaker_mapping_scores {
+
+    my ($spkr_map, $spkr_info) = @_;
+    my ($ref_spkr, $ref_type, $sys_spkr, $sys_type, %imap, %stats);
+
+    foreach $ref_spkr (keys %{$spkr_info->{REF}}) {
+	next unless $spkr_info->{REF}{$ref_spkr}{TIME};
+	$ref_type = $spkr_info->{REF}{$ref_spkr}{TYPE};
+	$stats{REF}{$ref_type}++;
+	$sys_spkr = $spkr_map->{$ref_spkr};
+	$sys_type = defined $sys_spkr ? $spkr_info->{SYS}{$sys_spkr}{TYPE} : $miss_name;
+	$stats{JOINT}{$ref_type}{$sys_type}++;
+	$imap{$sys_spkr} = $ref_spkr if defined $sys_spkr;
+    }
+    foreach $sys_spkr (keys %{$spkr_info->{SYS}}) {
+	next unless $spkr_info->{SYS}{$sys_spkr}{TIME};
+	$sys_type = $spkr_info->{SYS}{$sys_spkr}{TYPE};
+	$stats{SYS}{$sys_type}++;
+	$stats{JOINT}{$fa_name}{$sys_type}++
+	    unless defined $imap{$sys_spkr};
+    }
+    return {%stats};
+}
+
+#################################
+
+sub score_speaker_segments {
+
+    my ($stats, $score_segs, $ref_wds, $spkr_map, $spkr_info) = @_;
+    my ($ref_spkr, $ref_type, $sys_spkr, $sys_type, %type_stats);
+    my (@ref_wds, $wrd, $seg, $seg_dur, $nref, $nsys);
+
+    @ref_wds = @$ref_wds;
+    $wrd = shift @ref_wds;
+    foreach $seg (@$score_segs) {
+	$seg_dur = $seg->{TDUR};
+	$stats->{SCORED_TIME} += $seg_dur;
+	$nref = keys %{$seg->{REF}};
+	$nsys = keys %{$seg->{SYS}};
+	$stats->{SCORED_SPEECH} += $nref ? $seg_dur : 0;
+	$stats->{MISSED_SPEECH} += ($nref and not $nsys) ? $seg_dur : 0;
+	$stats->{FALARM_SPEECH} += ($nsys and not $nref) ? $seg_dur : 0;
+	$stats->{SCORED_SPEAKER} += $seg_dur*$nref;
+	$stats->{MISSED_SPEAKER} += $seg_dur*max($nref-$nsys,0);
+	$stats->{FALARM_SPEAKER} += $seg_dur*max($nsys-$nref,0);
+
+	my $scored_wrds = my $missed_wrds = my $error_wrds = 0;
+	$wrd = shift @ref_wds while ($wrd and $wrd->{TMID} < $seg->{TBEG});
+	while ($wrd and $wrd->{TMID} <= $seg->{TEND}) {
+	    next unless $wrd->{SCOREABLE};
+	    $scored_wrds++;
+	    $missed_wrds++ if not $nsys;
+	    $error_wrds++ unless speakers_match ($seg->{REF}, $seg->{SYS}, $spkr_map);
+	    $wrd = shift @ref_wds;
+	}
+	$stats->{SCORED_WORDS} += $scored_wrds;
+	$stats->{MISSED_WORDS} += $missed_wrds;
+	$stats->{ERROR_WORDS} += $error_wrds;
+
+	my $nmap = 0, my %num_types;
+	foreach $ref_spkr (keys %{$seg->{REF}}) {
+	    $ref_type = $spkr_info->{REF}{$ref_spkr}{TYPE};
+	    $num_types{REF}{$ref_type}++;
+	    $sys_spkr = $spkr_map->{$ref_spkr};
+	    $nmap++ if defined $sys_spkr and defined $seg->{SYS}{$sys_spkr};
+	}
+	$stats->{SPEAKER_ERROR} += $seg_dur*(min($nref,$nsys) - $nmap);
+
+	foreach $sys_spkr (keys %{$seg->{SYS}}) {
+	    $sys_type = $spkr_info->{SYS}{$sys_spkr}{TYPE};
+	    $num_types{SYS}{$sys_type}++;
+	}
+	foreach $ref_type (keys %{$num_types{REF}}) {
+	    $nref = $num_types{REF}{$ref_type};
+	    $type_stats{REF}{$ref_type} += $nref*$seg_dur;
+	    foreach $sys_type (keys %{$num_types{SYS}}) {
+		$nsys = $num_types{SYS}{$sys_type};
+		$type_stats{JOINT}{$ref_type}{$sys_type} += min($nref,$nsys)*$seg_dur;
+	    }
+	    $type_stats{JOINT}{$ref_type}{$miss_name} += max($nref-$nsys,0)*$seg_dur;
+	}
+	foreach $sys_type (keys %{$num_types{SYS}}) {
+	    $nsys = $num_types{SYS}{$sys_type};
+	    $type_stats{SYS}{$sys_type} += $nsys*$seg_dur;
+	    $type_stats{JOINT}{$fa_name}{$sys_type} += max($nsys-$nref,0)*$seg_dur;
+	}
+    }
+    $stats->{TYPE}{TIME} = {%type_stats};
+}
+
+#################################
+
+sub speakers_match {
+
+    my ($ref_spkrs, $sys_spkrs, $spkr_map) = @_;
+
+    return 0 unless keys %$ref_spkrs == keys %$sys_spkrs;
+    foreach my $ref_spkr (keys %$ref_spkrs) {
+	return 0 unless (defined $spkr_map->{$ref_spkr} and
+			 defined $sys_spkrs->{$spkr_map->{$ref_spkr}});
+    }
+    return 1;
+}
+
+#################################
+
+sub add_collars_to_uem {
+
+    my ($uem_eval, $ref_data) = @_;
+    my (@events, $event, $uem, $uem_score, $spkr, $spkr_seg, $tbeg, $evaluate);
+
+    foreach $uem (@$uem_eval) {
+	push @events, {EVENT => "BEG", TIME => $uem->{TBEG}};
+	push @events, {EVENT => "END", TIME => $uem->{TEND}};
+    }
+#add no-score collars
+    foreach $spkr (keys %$ref_data) {
+	foreach $spkr_seg (@{$ref_data->{$spkr}}) {
+	    push @events, {EVENT => "END", TIME => $spkr_seg->{TBEG}-$collar};
+	    push @events, {EVENT => "BEG", TIME => $spkr_seg->{TBEG}+$collar};
+	    push @events, {EVENT => "END", TIME => $spkr_seg->{TEND}-$collar};
+	    push @events, {EVENT => "BEG", TIME => $spkr_seg->{TEND}+$collar};
+	}
+    }
+    @events = sort {($a->{TIME} < $b->{TIME} ? -1 :
+		     ($a->{TIME} > $b->{TIME} ? 1 :
+		      $a->{EVENT} eq "END"))} @events;
+    $evaluate = 0;
+    foreach $event (@events) {
+	if ($event->{EVENT} eq "BEG") {
+	    $evaluate++;
+	    $tbeg = $event->{TIME} if $evaluate == 1;
+	}
+	else {
+	    $evaluate--;
+	    push @$uem_score, {TBEG => $tbeg, TEND => $event->{TIME}}
+	        if $evaluate == 0 and $event->{TIME} > $tbeg;
+	}
+    }
+    return $uem_score;
+}
+
+#################################
+
+sub exclude_overlapping_speech_from_uem {
+
+    my ($uem_data, $rttm_data) = @_;
+    my ($token, @spkr_events, $event, $spkr_cnt, $tbeg_overlap, $uem, @events, $uem_ex);
+
+#overlapping speech computed from SPEAKER data
+    foreach $token (@$rttm_data) {
+	next unless ($token->{TYPE} eq "SPEAKER" and
+		     $token->{TDUR} > 0);
+	push @spkr_events, {EVENT => "BEG", TIME => $token->{TBEG}, SPKR => $token->{SPKR}};
+	push @spkr_events, {EVENT => "END", TIME => $token->{TEND}, SPKR => $token->{SPKR}};
+    }
+    @spkr_events = sort {($a->{TIME} < $b->{TIME} ? -1 :
+			  ($a->{TIME} > $b->{TIME} ? 1 :
+			   $a->{EVENT} eq "BEG"))} @spkr_events;
+
+#create noscore zones
+    foreach $event (@spkr_events) {
+	if ($event->{EVENT} eq "BEG") {
+	    next unless ++$spkr_cnt == 2;
+	    $tbeg_overlap = $event->{TIME};
+	}
+	else {
+	    next unless --$spkr_cnt == 1;
+	    push @events, {TYPE => "NSZ", EVENT => "BEG", TIME => $tbeg_overlap};
+	    push @events, {TYPE => "NSZ", EVENT => "END", TIME => $event->{TIME}};
+	}
+    }
+
+#merge noscore zones with UEM data
+    foreach $uem (@$uem_data) {
+	next unless $uem->{TEND}-$uem->{TBEG} > 0;
+	push @events, {TYPE => "UEM", EVENT => "BEG", TIME => $uem->{TBEG}};
+	push @events, {TYPE => "UEM", EVENT => "END", TIME => $uem->{TEND}};
+    }
+    @events = sort {($a->{TIME} < $b->{TIME} ? -1 :
+		     ($a->{TIME} > $b->{TIME} ? 1 :
+		      $a->{EVENT} eq "BEG"))} @events;
+
+    my $tbeg = my $evl_cnt = my $nsz_cnt = my $evaluating = 0;
+    foreach $event (@events) {
+	$evl_cnt += $event->{EVENT} eq "BEG" ? 1 : -1 if $event->{TYPE} eq "UEM";
+	$nsz_cnt += $event->{EVENT} eq "BEG" ? 1 : -1 if $event->{TYPE} eq "NSZ";
+	if ($evaluating and
+	    ($evl_cnt == 0 or $nsz_cnt > 0) and
+	    $event->{TIME} > $tbeg) {
+	    push @$uem_ex, {TBEG => $tbeg, TEND => $event->{TIME}};
+	    $evaluating = 0;
+	}
+	elsif ($evl_cnt > 0 and $nsz_cnt == 0) {
+	    $tbeg = $event->{TIME};
+	    $evaluating = 1;
+	}
+    }
+
+    return $uem_ex;
+}
+
+#################################
+
+sub add_exclusion_zones_to_uem {
+
+    my ($excluded_tokens, $uem_score, $rttm_data, $max_extend) = @_;
+    my (@events, $event, $uem, $uem_ex, $spkr, $spkr_seg, $tbeg, $evaluating, $token);
+    my (@ns_events, $evl_cnt, $lex_cnt, $nsz_cnt, $tstart, $tstop);
+    my ($tbeg_lex, $tbeg_nsz, $tend_lex, $tend_nsz, $tseg);
+
+    return $uem_score unless defined $excluded_tokens and (keys %$excluded_tokens) > 0;
+
+#gather data needed to create noscore zones
+    foreach $token (@$rttm_data) {
+	if ($token->{TYPE} eq "LEXEME" and
+	    not defined $excluded_tokens->{LEXEME}{$token->{SUBT}} and
+	    $token->{TDUR} > 0) {
+	    push @ns_events, {TYPE => "LEX", EVENT => "BEG", TIME => $token->{TBEG}};
+	    push @ns_events, {TYPE => "LEX", EVENT => "END", TIME => $token->{TEND}};
+	}
+	elsif ($token->{TYPE} eq "SPEAKER" and
+	       $token->{TDUR} > 0) {
+	    push @ns_events, {TYPE => "SEG", EVENT => "BEG", TIME => $token->{TBEG}};
+	    push @ns_events, {TYPE => "SEG", EVENT => "END", TIME => $token->{TEND}};
+	}
+	elsif (defined $excluded_tokens->{$token->{TYPE}}{$token->{SUBT}} and
+	       $token->{TDUR} > 0) {
+	    push @ns_events, {TYPE => "NSZ", EVENT => "BEG", TIME => $token->{TBEG}};
+	    push @ns_events, {TYPE => "NSZ", EVENT => "END", TIME => $token->{TEND}};
+	}
+    }
+    @ns_events = sort {($a->{TIME} < $b->{TIME} ? -1 :
+			($a->{TIME} > $b->{TIME} ? 1 :
+			 $a->{EVENT} eq "BEG"))} @ns_events;
+
+#create noscore zones
+    $evaluating = 1;
+    $max_extend = $epsilon if not $max_extend or $max_extend < $epsilon;
+    $tseg = $tbeg_nsz = $tbeg_lex = $tend_nsz = $tend_lex = 0;
+    $lex_cnt = $nsz_cnt = 0;
+    foreach $event (@ns_events) {
+	if ($event->{TYPE} eq "LEX") {
+	    if ($event->{EVENT} eq "BEG") {
+		$tbeg_lex = $event->{TIME} if $lex_cnt++ == 0;
+	    }
+	    else {
+		$tend_lex = $event->{TIME} if $lex_cnt-- == 1;
+	    }
+	}
+	elsif ($event->{TYPE} eq "NSZ") {
+	    if ($event->{EVENT} eq "BEG") {
+		$tbeg_nsz = $event->{TIME} if $nsz_cnt++ == 0;
+	    }
+	    else {
+		$tend_nsz = $event->{TIME} if $nsz_cnt-- == 1;
+	    }
+	}
+	elsif ($event->{TYPE} eq "SEG") {
+	    $tseg = $event->{TIME};
+	}
+
+	if ($evaluating) {
+	    next if ($nsz_cnt == 0 or
+		     $event->{TYPE} ne "NSZ");
+	    $tstop = ($lex_cnt > 0 ? $event->{TIME} :
+		      max($tend_lex, $tseg, $event->{TIME}-$max_extend));
+	    push @events, {TYPE => "NSZ", EVENT => "BEG", TIME => $tstop};
+	    $evaluating = 0;
+	}
+	elsif ($nsz_cnt == 0 and
+	       ($lex_cnt > 0 or
+		$event->{TYPE} eq "SEG")) {
+	    $tstart = min($tend_nsz+$max_extend, $event->{TIME});
+	    push @events, {TYPE => "NSZ", EVENT => "END", TIME => $tstart};
+	    $evaluating = 1;
+	}
+	elsif ($nsz_cnt == 1 and
+	       $event->{TYPE} eq "NSZ" and
+	       $event->{EVENT} eq "BEG" and
+	       $event->{TIME} > $tend_nsz+2*$max_extend) {
+	    push @events, {TYPE => "NSZ", EVENT => "END", TIME => $tend_nsz+$max_extend};
+	    push @events, {TYPE => "NSZ", EVENT => "BEG", TIME => $event->{TIME}-$max_extend};
+	    $evaluating = 0;
+	}
+    }
+
+#merge noscore zones with UEM data
+    foreach $uem (@$uem_score) {
+	next unless $uem->{TEND}-$uem->{TBEG} > 0;
+	push @events, {TYPE => "UEM", EVENT => "BEG", TIME => $uem->{TBEG}};
+	push @events, {TYPE => "UEM", EVENT => "END", TIME => $uem->{TEND}};
+    }
+    @events = sort {($a->{TIME} < $b->{TIME} ? -1 :
+		     ($a->{TIME} > $b->{TIME} ? 1 :
+		      $a->{EVENT} eq "BEG"))} @events;
+    $evl_cnt = $evaluating = 0;
+    foreach $event (@events) {
+	$evl_cnt += $event->{EVENT} eq "BEG" ? 1 : -1 if $event->{TYPE} eq "UEM";
+	$nsz_cnt += $event->{EVENT} eq "BEG" ? 1 : -1 if $event->{TYPE} eq "NSZ";
+	if ($evaluating and
+	    ($evl_cnt == 0 or $nsz_cnt > 0) and
+	    $event->{TIME} > $tbeg) {
+	    push @$uem_ex, {TBEG => $tbeg, TEND => $event->{TIME}};
+	    $evaluating = 0;
+	}
+	elsif ($evl_cnt > 0 and $nsz_cnt == 0) {
+	    $tbeg = $event->{TIME};
+	    $evaluating = 1;
+	}
+    }
+
+    return $uem_ex;
+}
+
+#################################
+
+sub uem_from_rttm {
+
+    my ($rttm_data) = @_;
+    my ($token, $tbeg, $tend);
+
+    ($tbeg, $tend) = (1E30, 0);
+    foreach $token (@$rttm_data) {
+	($tbeg, $tend) = (min($tbeg,$token->{TBEG}), max($tend,$token->{TEND})) if
+	    $token->{TYPE} =~ /^(SEGMENT|SPEAKER|SU|EDIT|FILLER|IP|CB|A\/P|LEXEME|NON-LEX)$/;
+    }
+
+    return [{TBEG => $tbeg, TEND => $tend}];
+}
+
+#################################
+
+sub create_speaker_segs {
+
+    my ($uem_score, $ref_data, $sys_data) = @_;
+    my ($spkr, $seg, @events, $event, $uem, $segments, $tbeg, $tend);
+    my ($evaluate, %ref_spkrs, %sys_spkrs, $spkrs);
+
+    foreach $uem (@$uem_score) {
+	next unless $uem->{TEND} > $uem->{TBEG}+$epsilon;
+	push @events, {TYPE => "UEM", EVENT => "BEG", TIME => $uem->{TBEG}};
+	push @events, {TYPE => "UEM", EVENT => "END", TIME => $uem->{TEND}};
+    }
+    foreach $spkr (keys %$ref_data) {
+	foreach $seg (@{$ref_data->{$spkr}}) {
+	    next unless $seg->{TDUR} > 0;
+	    push @events, {TYPE => "REF", SPKR => $spkr, EVENT => "BEG", TIME => $seg->{TBEG}};
+	    push @events, {TYPE => "REF", SPKR => $spkr, EVENT => "END", TIME => $seg->{TEND}};
+	}
+    }
+    foreach $spkr (keys %$sys_data) {
+	foreach $seg (@{$sys_data->{$spkr}}) {
+	    next unless $seg->{TDUR} > 0;
+	    push @events, {TYPE => "SYS", SPKR => $spkr, EVENT => "BEG", TIME => $seg->{RTBEG}};
+	    push @events, {TYPE => "SYS", SPKR => $spkr, EVENT => "END", TIME => $seg->{RTEND}};
+	}
+    }
+    @events = sort {($a->{TIME} < $b->{TIME}-$epsilon  ? -1 :
+		     ($a->{TIME} > $b->{TIME}+$epsilon ?  1 :
+		      ($a->{EVENT} eq "END"        ? -1 : 1)))} @events;
+    $evaluate = 0;
+    foreach $event (@events) {
+	if ($evaluate and $tbeg<$event->{TIME}) {
+	    $tend = $event->{TIME};
+	    push @$segments, {REF => {%ref_spkrs},
+			      SYS => {%sys_spkrs},
+			      TBEG => $tbeg,
+			      TEND => $tend,
+			      TDUR => $tend-$tbeg};
+	    $tbeg = $tend;
+	}
+	if ($event->{TYPE} eq "UEM") {
+	    $evaluate = $event->{EVENT} eq "BEG";
+	    $tbeg = $event->{TIME} if $evaluate;
+	}
+	else {
+	    $spkrs = $event->{TYPE} eq "REF" ? \%ref_spkrs : \%sys_spkrs;
+	    ($event->{EVENT} eq "BEG") ? $spkrs->{$event->{SPKR}}++ : $spkrs->{$event->{SPKR}}--;
+	    $spkrs->{$event->{SPKR}} <= 1 or warn
+	        "WARNING:  speaker $event->{SPKR} speaking more than once at time $event->{TIME}\n";
+	    delete $spkrs->{$event->{SPKR}} unless $spkrs->{$event->{SPKR}};
+	}
+    }
+    return $segments;
+}
+
+#################################
+
+sub sd_performance_analysis {
+
+    my ($scores, $subtypes) = @_;
+    my ($file, $chnl, $class, $kind, $ref_type, $sys_type);
+    my ($xscores, %cum_scores, $count);
+
+#accumulate statistics
+    foreach $file (keys %$scores) {
+	foreach $chnl (keys %{$scores->{$file}}) {
+	    $xscores = $scores->{$file}{$chnl};
+	    foreach $ref_type (keys %$xscores) {
+		next if $ref_type eq "TYPE";
+		$count = $xscores->{$ref_type};
+		$cum_scores{ALL}{$ref_type} += $count;
+		$cum_scores{"c=$chnl f=$file"}{$ref_type} += $xscores->{$ref_type} if $opt_a =~ /c/i and $opt_a =~ /f/i;
+		$cum_scores{"c=$chnl"}{$ref_type} += $xscores->{$ref_type} if $opt_a =~ /c/i and not $opt_a =~ /f/i;
+		$cum_scores{"f=$file"}{$ref_type} += $xscores->{$ref_type} if $opt_a =~ /f/i and not $opt_a =~ /c/i;
+	    }
+	    $xscores = $xscores->{TYPE};
+	    foreach my $class ("TIME", "NSPK") {
+		foreach my $kind ("REF", "SYS") {
+		    foreach $ref_type (keys %{$xscores->{$class}{$kind}}) {
+			$count = $xscores->{$class}{$kind}{$ref_type};
+			$cum_scores{ALL}{TYPE}{$class}{$kind}{$ref_type} += $count;
+			$cum_scores{"c=$chnl f=$file"}{TYPE}{$class}{$kind}{$ref_type} += $count if $opt_a =~ /c/i and $opt_a =~ /f/i;
+			$cum_scores{"c=$chnl"}{TYPE}{$class}{$kind}{$ref_type} += $count if $opt_a =~ /c/i and not $opt_a =~ /f/i;
+			$cum_scores{"f=$file"}{TYPE}{$class}{$kind}{$ref_type} += $count if $opt_a =~ /f/i and not $opt_a =~ /c/i;
+		    }
+		}
+		foreach $ref_type (keys %{$xscores->{$class}{JOINT}}) {
+		    foreach $sys_type (keys %{$xscores->{$class}{JOINT}{$ref_type}}) {
+			$count = $xscores->{$class}{JOINT}{$ref_type}{$sys_type};
+			$cum_scores{ALL}{TYPE}{$class}{JOINT}{$ref_type}{$sys_type} += $count;
+			$cum_scores{"c=$chnl f=$file"}{TYPE}{$class}{JOINT}{$ref_type}{$sys_type} += $count if $opt_a =~ /c/i and $opt_a =~ /f/i;
+			$cum_scores{"c=$chnl"}{TYPE}{$class}{JOINT}{$ref_type}{$sys_type} += $count if $opt_a =~ /c/i and not $opt_a =~ /f/i;
+			$cum_scores{"f=$file"}{TYPE}{$class}{JOINT}{$ref_type}{$sys_type} += $count if $opt_a =~ /f/i and not $opt_a =~ /c/i;
+		    }
+		}
+	    }
+	}
+    }
+
+    foreach my $condition (sort keys %cum_scores) {
+	print_sd_scores ($condition, $cum_scores{$condition}) if $condition !~ /ALL/;
+    }
+    print_sd_scores ("ALL", $cum_scores{ALL});
+}
+
+#################################
+
+sub print_sd_scores {
+
+    my ($condition, $scores) = @_;
+
+    printf "\n*** Performance analysis for Speaker Diarization for $condition ***\n\n";
+
+    #printf "    EVAL TIME =%10.2f secs\n", $scores->{EVAL_TIME};
+    #printf "  EVAL SPEECH =%10.2f secs (%5.1f percent of evaluated time)\n", $scores->{EVAL_SPEECH},
+    #    100*$scores->{EVAL_SPEECH}/$scores->{EVAL_TIME};
+    #printf "  SCORED TIME =%10.2f secs (%5.1f percent of evaluated time)\n",
+    #    $scores->{SCORED_TIME}, 100*$scores->{SCORED_TIME}/$scores->{EVAL_TIME};
+    #printf "SCORED SPEECH =%10.2f secs (%5.1f percent of scored time)\n",
+    #    $scores->{SCORED_SPEECH}, 100*$scores->{SCORED_SPEECH}/$scores->{SCORED_TIME};
+    #printf "   EVAL WORDS =%7d        \n", $scores->{EVAL_WORDS};
+    #printf " SCORED WORDS =%7d         (%5.1f percent of evaluated words)\n",
+    #    $scores->{SCORED_WORDS}, 100*$scores->{SCORED_WORDS}/$scores->{EVAL_WORDS};
+    #print "---------------------------------------------\n";
+    #printf "MISSED SPEECH =%10.2f secs (%5.1f percent of scored time)\n",
+    ##    $scores->{MISSED_SPEECH}, 100*$scores->{MISSED_SPEECH}/$scores->{SCORED_TIME};
+    #printf "FALARM SPEECH =%10.2f secs (%5.1f percent of scored time)\n",
+    #    $scores->{FALARM_SPEECH}, 100*$scores->{FALARM_SPEECH}/$scores->{SCORED_TIME};
+    #printf " MISSED WORDS =%7d         (%5.1f percent of scored words)\n",
+    #    $scores->{MISSED_WORDS}, 100*$scores->{MISSED_WORDS}/$scores->{SCORED_WORDS};
+    #print "---------------------------------------------\n";
+    #printf "SCORED SPEAKER TIME =%10.2f secs (%5.1f percent of scored speech)\n",
+    #    $scores->{SCORED_SPEAKER}, 100*$scores->{SCORED_SPEAKER}/$scores->{SCORED_SPEECH};
+    #printf "MISSED SPEAKER TIME =%10.2f secs (%5.1f percent of scored speaker time)\n",
+    #    $scores->{MISSED_SPEAKER}, 100*$scores->{MISSED_SPEAKER}/$scores->{SCORED_SPEAKER};
+    #printf "FALARM SPEAKER TIME =%10.2f secs (%5.1f percent of scored speaker time)\n",
+    #    $scores->{FALARM_SPEAKER}, 100*$scores->{FALARM_SPEAKER}/$scores->{SCORED_SPEAKER};
+    #printf " SPEAKER ERROR TIME =%10.2f secs (%5.1f percent of scored speaker time)\n",
+    #    $scores->{SPEAKER_ERROR}, 100*$scores->{SPEAKER_ERROR}/$scores->{SCORED_SPEAKER};
+    #printf "SPEAKER ERROR WORDS =%7d         (%5.1f percent of scored speaker words)\n",
+    #    $scores->{ERROR_WORDS}, 100*$scores->{ERROR_WORDS}/$scores->{SCORED_WORDS};
+    #print "---------------------------------------------\n";
+    #
+    #
+    #
+    printf "SCORED SPEAKER TIME =%f secs\n", $scores->{SCORED_SPEAKER};
+    printf "MISSED SPEAKER TIME =%f secs\n", $scores->{MISSED_SPEAKER};
+    printf "FALARM SPEAKER TIME =%f secs\n", $scores->{FALARM_SPEAKER};
+    printf "SPEAKER ERROR TIME =%f secs\n", $scores->{SPEAKER_ERROR};
+#    if ($condition eq "ALL") {
+#      printf " OVERALL SPEAKER DIARIZATION ERROR = %.2f percent of scored speaker time\n",
+#         100*($scores->{MISSED_SPEAKER} + $scores->{FALARM_SPEAKER} + $scores->{SPEAKER_ERROR})/
+#	    $scores->{SCORED_SPEAKER};
+#    } else {
+      printf " OVERALL SPEAKER DIARIZATION ERROR = %.2f percent of scored speaker time  %s\n",
+         100*($scores->{MISSED_SPEAKER} + $scores->{FALARM_SPEAKER} + $scores->{SPEAKER_ERROR})/
+    	    $scores->{SCORED_SPEAKER}, "`($condition)";
+#    }
+    print "---------------------------------------------\n";
+    printf " Speaker type confusion matrix -- speaker weighted\n";
+    summarize_speaker_type_performance ("NSPK", $scores->{TYPE}{NSPK});
+    print "---------------------------------------------\n";
+    printf " Speaker type confusion matrix -- time weighted\n";
+    summarize_speaker_type_performance ("TIME", $scores->{TYPE}{TIME});
+    print "---------------------------------------------\n";
+}
+
+#################################
+
+sub summarize_speaker_type_performance {
+
+    my ($class, $stats) = @_;
+    my ($ref_type, $sys_type, $sys_stat);
+
+    print "  REF\\SYS (count)      " if $class eq "NSPK";
+    print "  REF\\SYS (seconds)    " if $class eq "TIME";
+    foreach $sys_type ((sort keys %{$stats->{SYS}}), $miss_name) {
+	printf "%-20s", $sys_type;
+    }
+    print "\n";
+
+    my $ref_tot = 0;
+    foreach $ref_type (keys %{$stats->{REF}}) {
+	$ref_tot += $stats->{REF}{$ref_type};
+    }
+
+    foreach $ref_type ((sort keys %{$stats->{REF}}), $fa_name) {
+	printf "%-16s", $ref_type;
+	foreach $sys_type ((sort keys %{$stats->{SYS}}), $miss_name) {
+	    next if $ref_type eq $fa_name and $sys_type eq $miss_name;
+	    $sys_stat = $stats->{JOINT}{$ref_type}{$sys_type};
+	    $sys_stat = 0 unless defined $sys_stat;
+	    printf "%11d /%6.1f",   $sys_stat, min(999.9,$ref_tot ? 100*$sys_stat/$ref_tot : 9E9) if $class eq "NSPK";
+	    printf "%11.2f /%6.1f", $sys_stat, min(999.9,$ref_tot ? 100*$sys_stat/$ref_tot : 9E9) if $class eq "TIME";
+	    print "%";
+	}
+	print "\n";
+    }
+}
+
+#################################
+
+sub map_speakers {
+
+    my ($spkr_overlap) = @_;
+
+#compute the costs
+    my $cost = {};
+    foreach my $ref_spkr (keys %$spkr_overlap) {
+	foreach my $sys_spkr (keys %{$spkr_overlap->{$ref_spkr}}) {
+	    $cost->{$ref_spkr}{$sys_spkr} = -$spkr_overlap->{$ref_spkr}{$sys_spkr};
+	}
+    }
+
+#find the mapping that maximizes the cumulative match time between ref and sys spkrs
+    my $map = weighted_bipartite_graph_match ($cost);
+    return $map;
+}
+
+#################################
+
+sub inverse_speaker_map {
+
+    my ($speaker_map) = @_;
+    my ($speaker, $inverse_speaker_map);
+
+    foreach $speaker (keys %$speaker_map) {
+	$inverse_speaker_map->{$speaker_map->{$speaker}} = $speaker;
+    }
+    return $inverse_speaker_map;
+}
+
+#################################
+
+sub print_speaker_map {
+
+    my ($spkr_map, $time_overlap) = @_;
+    my ($ref_spkr, $sys_spkr);
+
+    foreach $ref_spkr (sort keys %$time_overlap) {
+	$sys_spkr = $spkr_map->{$ref_spkr};
+	print "'$ref_spkr' => ", defined $sys_spkr ? "'$sys_spkr'\n" : "<nil>\n";
+	foreach $sys_spkr (sort keys %{$time_overlap->{$ref_spkr}}) {
+	    my $time = $time_overlap->{$ref_spkr}{$sys_spkr};
+	    printf "%9.2f secs matched to '$sys_spkr'\n", defined $time ? $time : 0;
+	}
+    }
+}
+
+#################################
+
+sub start_speaker_map_file {
+    my ($outFile) = @_;
+    open (FILE, ">$outFile") || die "Error: Unable to open speaker map CSV file '$outFile' for write";
+    print FILE "File,Channel,RefSpeaker,SysSpeaker,isMapped,timeOverlap\n";
+    close FILE;
+}
+
+#################################
+
+sub update_speaker_map_file {
+
+    my ($spkr_map, $time_overlap, $file, $chnl, $outFile) = @_;
+
+    open (FILE, ">>$outFile") || die "Error: Failed to open speaker map CSV file '$outFile' for append";
+    foreach my $ref_spkr (sort keys %$time_overlap) {
+	foreach my $sys_spkr (sort keys %{$time_overlap->{$ref_spkr}}) {
+	    my $time = sprintf("%.4f",$time_overlap->{$ref_spkr}{$sys_spkr});
+	    print FILE "$file,$chnl,$ref_spkr,$sys_spkr";
+	    print FILE ",".((defined($spkr_map->{$ref_spkr}) && $sys_spkr eq $spkr_map->{$ref_spkr}) ? "mapped" : "notmapped");
+	    print FILE ",$time\n";
+	}
+    }
+    close FILE,
+}
+
+#################################
+
+sub print_speaker_segs {
+
+    my ($segs, $file, $chnl) = @_;
+    my ($seg, @segs, $spkr, $sep);
+
+    @segs = @$segs;
+    while ($seg = shift @segs) {
+	printf "beg/dur/end = %7.3f/%7.3f/%7.3f; REF = (", $seg->{TBEG}, $seg->{TDUR}, $seg->{TEND};
+	print "<none>" unless defined keys %{$seg->{REF}};
+	$sep = "";
+	foreach $spkr (sort keys %{$seg->{REF}}) {
+	    print "$sep$spkr";
+	    $sep = ", ";
+	}
+	print "); SYS = (";
+	$sep = "";
+	print "<none>" unless defined keys %{$seg->{SYS}};
+	foreach $spkr (sort keys %{$seg->{SYS}}) {
+	    print "$sep$spkr";
+	    $sep = ", ";
+	}
+	print "); file = $file; chnl = $chnl\n";
+    }
+}
+
+#################################
+
+sub sort_time {
+
+    my ($token, $key) = @_;
+
+    my $time = $token->{"R$key"};
+    $time = $token->{$key} if not defined $time;
+    return int(100*$time+0.5)/100
+}
+
+#################################
+
+sub display_metadata_mapping {
+
+    my ($file, $chnl, $ref_rttm, $sys_rttm, $ref_wds) = @_;
+    my ($type, $sys_token, @events, $event, %type_cnt);
+    my ($mapped, $beg_mapped, $end_mapped, $whole, $spkr_map, $sys_speaker_field);
+    my %ref_tag = (NOSCORE        => "XS", NO_RT_METADATA => "NM", SEGMENT        => "SG", SPEAKER        => "SP",
+		   SU             => "SU", "A/P"          => "AP", "NON-SPEECH"   => "NS", EDIT           => "ED",
+		   FILLER         => "FL", IP             => "IP", CB             => "CB", "NON-LEX"      => "NL",
+		   LEXEME         => "LX");
+    my %sys_tag = (SPEAKER        => "SP", SU             => "SU", EDIT           => "ED", FILLER         => "FL",
+		   IP             => "IP", LEXEME         => "LX");
+
+#create a vector of rttm events
+    foreach my $token (@$ref_rttm) {
+	next unless defined $ref_tag{$token->{TYPE}};
+	push @events, {EVENT => "BEG", TIME => sort_time ($token, "TBEG"), TYPE => $token->{TYPE}, SRC => "REF", TOKEN => $token};
+	push @events, {EVENT => "END", TIME => sort_time ($token, "TEND"), TYPE => $token->{TYPE}, SRC => "REF", TOKEN => $token}
+	    unless $token->{TYPE} =~ /^(IP|CB)$/;
+	$token->{COUNT} = ++$type_cnt{$token->{TYPE}};
+    }
+    foreach my $token (@$sys_rttm) {
+	next unless defined $sys_tag{$token->{TYPE}};
+	push @events, {EVENT => "BEG", TIME => sort_time ($token, "TBEG"), TYPE => $token->{TYPE}, SRC => "SYS", TOKEN => $token};
+	push @events, {EVENT => "END", TIME => sort_time ($token, "TEND"), TYPE => $token->{TYPE}, SRC => "SYS", TOKEN => $token}
+	    unless $token->{TYPE} =~ /^(IP|CB)$/;
+    }
+
+    @events = sort sort_events @events;
+
+    $spkr_map = inverse_speaker_map ($speaker_map{$file}{$chnl});
+
+    print "\nChronological display of sys data aligned with ref data for file '$file', channel '$chnl'\n";
+    print "----------------------- reference ----------------------- | mapped | --------------------- system output ---------------------\n";
+    print "    --type-- -subtyp- -----word/spkr-----  -tbeg-  -tend- | ref_ID |     --type-- -subtyp- -----word/spkr-----  -tbeg-  -tend-\n";
+
+    while (@events) {
+        my ($token, $ref, $ref_beg, $ref_end, $sys, $sys_beg, $sys_end);
+	while (@events and
+	       (not $token or
+		$token eq $events[0]->{TOKEN} or
+		($events[0]->{TOKEN}{MAPPTR} and
+		 $token eq $events[0]->{TOKEN}{MAPPTR}))) { # collect events to display on the same line
+	    $event = shift @events;
+	    $token = $event->{TOKEN};
+	    $event->{SRC} eq "REF" ? ($ref = $token, ($event->{EVENT} eq "BEG" ? $ref_beg : $ref_end) = 1) :
+	                             ($sys = $token, ($event->{EVENT} eq "BEG" ? $sys_beg : $sys_end) = 1);
+	}
+	if ($ref) {
+	    printf "%-3.3s %-8.8s %-8.8s %-19.19s%8s%8s | %-6.6s |",
+	    (($ref->{TYPE} =~ /^(IP|CB)$/ or ($ref_beg and $ref_end)) ? "" : ($ref_beg ? "beg" : "end")),
+	    $ref->{TYPE}, $ref->{SUBT},
+	    $ref->{WORD} ne "<na>" ? uc $ref->{WORD} : $ref->{SPKR},
+	    $ref_beg ? (sprintf "%8.2f", $ref->{TBEG}) : "",
+	    $ref_end ? (sprintf "%8.2f", $ref->{TEND}) : "",
+	    $ref->{MAPPTR} ? (sprintf "%s%d", $ref_tag{$ref->{TYPE}}, $ref->{COUNT}) :
+		($md_subtypes{$ref->{TYPE}} ? "*Miss*" : "");
+	} elsif ($sys) {
+	    $ref = $sys->{MAPPTR};
+	    printf "%s%8s%8s | %-6.6s |", " "x41,
+	    $sys_beg ? (sprintf "%8.2f", defined $sys->{RTBEG} ? $sys->{RTBEG} : $sys->{TBEG}) : "",
+	    $sys_end ? (sprintf "%8.2f", defined $sys->{RTEND} ? $sys->{RTEND} : $sys->{TEND}) : "",
+	    $ref ? (sprintf "%s%d", $sys_tag{$ref->{TYPE}}, $ref->{COUNT}) :
+		($md_subtypes{$sys->{TYPE}} ? "**FA**" : "");
+	}
+	if ($sys) {
+	    $sys_speaker_field = $sys ? $sys->{SPKR} : "";
+	    $sys_speaker_field .= "=>$spkr_map->{$sys->{SPKR}}" if $spkr_map->{$sys->{SPKR}};
+	    printf "%3.3s %-8.8s %-8.8s %-19.19s%8s%8s",
+	    (($sys->{TYPE} =~ /^(IP|CB)$/ or ($sys_beg and $sys_end)) ? "" : ($sys_beg ? "beg" : "end")),
+	    $sys->{TYPE}, $sys->{SUBT},
+	    $sys->{WORD} ne "<na>" ? uc $sys->{WORD} : $sys_speaker_field,
+	    $sys_beg ? (sprintf "%8.2f", $sys->{TBEG}) : "",
+	    $sys_end ? (sprintf "%8.2f", $sys->{TEND}) : "";
+	    if ($md_subtypes{$sys->{TYPE}} and $ref = $sys->{MAPPTR}) {
+		my $dw = $sys_end ?
+		    ($ref->{WEND} <= $sys->{RWEND} ?
+		     delta_metadata_error_words ("END", max($ref->{WEND}, $sys->{RWBEG}-1), $sys->{RWEND}, $ref_wds) :
+		     delta_metadata_error_words ("END", $ref->{WEND}, max($ref->{WBEG}-1, $sys->{RWEND}), $ref_wds)) :
+		    ($ref->{WBEG} <= $sys->{RWBEG} ?
+		     delta_metadata_error_words ("BEG", $ref->{WBEG}, min(1+$ref->{WEND}, $sys->{RWBEG}), $ref_wds) :
+		     delta_metadata_error_words ("BEG", min($ref->{WBEG}, 1+$sys->{RWEND}), $sys->{RWBEG}, $ref_wds));
+		print " dw=$dw" if abs ($dw) > 0;
+	    }
+	}
+	print "\n";
+    }
+}
+
+#################################
+
+sub sort_events {
+
+    return ($a->{TIME} <=> $b->{TIME} or
+	    $event_order{$a->{EVENT}} <=> $event_order{$b->{EVENT}} or
+	    (($type_order{$a->{TYPE}} <=> $type_order{$b->{TYPE}})*($a->{EVENT} eq "END" ? -1 : 1)) or
+	    $source_order{$a->{SRC}} <=> $source_order{$b->{SRC}});
+}
+
+#################################
+
+sub weighted_bipartite_graph_match {
+    my ($score) = @_;
+
+    my $required_precision = 1E-12;
+    my $INF = 1E30;
+    my (@row_mate, @col_mate, @row_dec, @col_inc);
+    my (@parent_row, @unchosen_row, @slack_row, @slack);
+    my ($k, $l, $row, $col, @col_min, $cost, %cost);
+    my $t = 0;
+
+    unless (defined $score) {
+	warn "input to BGM is undefined\n";
+	return undef;
+    }
+    return {} if (keys %$score) == 0;
+
+    my @rows = sort keys %{$score};
+    my $miss = "miss";
+    $miss .= "0" while exists $score->{$miss};
+    my (@cols, %cols);
+    my $min_score = $INF;
+    foreach $row (@rows) {
+	foreach $col (keys %{$score->{$row}}) {
+	    $min_score = min($min_score,$score->{$row}{$col});
+	    $cols{$col} = $col;
+	}
+    }
+    @cols = sort keys %cols;
+    my $fa = "fa";
+    $fa .= "0" while exists $cols{$fa};
+    my $reverse_search = @rows < @cols; # search is faster when ncols <= nrows
+    foreach $row (@rows) {
+	foreach $col (keys %{$score->{$row}}) {
+	    ($reverse_search ? $cost{$col}{$row} : $cost{$row}{$col})
+		= $score->{$row}{$col} - $min_score;
+	}
+    }
+    push @rows, $miss;
+    push @cols, $fa;
+    if ($reverse_search) {
+	my @xr = @rows;
+	@rows = @cols;
+	@cols = @xr;
+    }
+
+    my $nrows = @rows;
+    my $ncols = @cols;
+    my $nmax = max($nrows,$ncols);
+    my $no_match_cost = -$min_score*(1+$required_precision);
+
+    # subtract the column minimas
+    for ($l=0; $l<$nmax; $l++) {
+	$col_min[$l] = $no_match_cost;
+	next unless $l < $ncols;
+	$col = $cols[$l];
+	foreach $row (keys %cost) {
+	    next unless defined $cost{$row}{$col};
+	    my $val = $cost{$row}{$col};
+	    $col_min[$l] = $val if $val < $col_min[$l];
+	}
+    }
+
+    # initial stage
+    for ($l=0; $l<$nmax; $l++) {
+	$col_inc[$l] = 0;
+	$slack[$l] = $INF;
+    }
+
+  ROW:
+    for ($k=0; $k<$nmax; $k++) {
+	$row = $k < $nrows ? $rows[$k] : undef;
+	my $row_min = $no_match_cost;
+	for (my $l=0; $l<$ncols; $l++) {
+	    my $col = $cols[$l];
+	    my $val = ((defined $row and defined $cost{$row}{$col}) ? $cost{$row}{$col}: $no_match_cost) - $col_min[$l];
+	    $row_min = $val if $val < $row_min;
+	}
+	$row_dec[$k] = $row_min;
+	for ($l=0; $l<$nmax; $l++) {
+	    $col = $l < $ncols ? $cols[$l]: undef;
+	    $cost = ((defined $row and defined $col and defined $cost{$row}{$col}) ?
+		     $cost{$row}{$col} : $no_match_cost) - $col_min[$l];
+	    if ($cost==$row_min and not defined $row_mate[$l]) {
+		$col_mate[$k] = $l;
+		$row_mate[$l] = $k;
+                # matching row $k with column $l
+		next ROW;
+	    }
+	}
+	$col_mate[$k] = -1;
+	$unchosen_row[$t++] = $k;
+    }
+
+    goto CHECK_RESULT if $t == 0;
+
+    my $s;
+    my $unmatched = $t;
+    # start stages to get the rest of the matching
+    while (1) {
+	my $q = 0;
+
+	while (1) {
+	    while ($q < $t) {
+		# explore node q of forest; if matching can be increased, update matching
+		$k = $unchosen_row[$q];
+		$row = $k < $nrows ? $rows[$k] : undef;
+		$s = $row_dec[$k];
+		for ($l=0; $l<$nmax; $l++) {
+		    if ($slack[$l]>0) {
+			$col = $l < $ncols ? $cols[$l]: undef;
+			$cost = ((defined $row and defined $col and defined $cost{$row}{$col}) ?
+				 $cost{$row}{$col} : $no_match_cost) - $col_min[$l];
+			my $del = $cost - $s + $col_inc[$l];
+			if ($del < $slack[$l]) {
+			    if ($del == 0) {
+				goto UPDATE_MATCHING unless defined $row_mate[$l];
+				$slack[$l] = 0;
+				$parent_row[$l] = $k;
+				$unchosen_row[$t++] = $row_mate[$l];
+			    }
+			    else {
+				$slack[$l] = $del;
+				$slack_row[$l] = $k;
+			    }
+			}
+		    }
+		}
+
+		$q++;
+	    }
+
+	    # introduce a new zero into the matrix by modifying row_dec and col_inc
+	    # if the matching can be increased update matching
+	    $s = $INF;
+	    for ($l=0; $l<$nmax; $l++) {
+		if ($slack[$l] and ($slack[$l]<$s)) {
+		    $s = $slack[$l];
+		}
+	    }
+	    for ($q = 0; $q<$t; $q++) {
+		$row_dec[$unchosen_row[$q]] += $s;
+	    }
+
+	    for ($l=0; $l<$nmax; $l++) {
+		if ($slack[$l]) {
+		    $slack[$l] -= $s;
+		    if ($slack[$l]==0) {
+			# look at a new zero and update matching with col_inc uptodate if there's a breakthrough
+			$k = $slack_row[$l];
+			unless (defined $row_mate[$l]) {
+			    for (my $j=$l+1; $j<$nmax; $j++) {
+				if ($slack[$j]==0) {
+				    $col_inc[$j] += $s;
+				}
+			    }
+			    goto UPDATE_MATCHING;
+			}
+			else {
+			    $parent_row[$l] = $k;
+			    $unchosen_row[$t++] = $row_mate[$l];
+			}
+		    }
+		}
+		else {
+		    $col_inc[$l] += $s;
+		}
+	    }
+	}
+
+      UPDATE_MATCHING:  # update the matching by pairing row k with column l
+	while (1) {
+	    my $j = $col_mate[$k];
+	    $col_mate[$k] = $l;
+	    $row_mate[$l] = $k;
+            # matching row $k with column $l
+	    last UPDATE_MATCHING if $j < 0;
+	    $k = $parent_row[$j];
+	    $l = $j;
+	}
+
+	$unmatched--;
+	goto CHECK_RESULT if $unmatched == 0;
+
+	$t = 0;  # get ready for another stage
+	for ($l=0; $l<$nmax; $l++) {
+	    $parent_row[$l] = -1;
+	    $slack[$l] = $INF;
+	}
+	for ($k=0; $k<$nmax; $k++) {
+	    $unchosen_row[$t++] = $k if $col_mate[$k] < 0;
+	}
+    }  # next stage
+
+  CHECK_RESULT:  # rigorously check results before handing them back
+    for ($k=0; $k<$nmax; $k++) {
+	$row = $k < $nrows ? $rows[$k] : undef;
+	for ($l=0; $l<$nmax; $l++) {
+	    $col = $l < $ncols ? $cols[$l]: undef;
+	    $cost = ((defined $row and defined $col and defined $cost{$row}{$col}) ?
+		     $cost{$row}{$col} : $no_match_cost) - $col_min[$l];
+	    if ($cost < ($row_dec[$k] - $col_inc[$l])) {
+		next unless $cost < ($row_dec[$k] - $col_inc[$l]) - $required_precision*max(abs($row_dec[$k]),abs($col_inc[$l]));
+		warn "BGM: this cannot happen: cost{$row}{$col} ($cost) cannot be less than row_dec{$row} ($row_dec[$k]) - col_inc{$col} ($col_inc[$l])\n";
+		return undef;
+	    }
+	}
+    }
+
+    for ($k=0; $k<$nmax; $k++) {
+	$row = $k < $nrows ? $rows[$k] : undef;
+	$l = $col_mate[$k];
+	$col = $l < $ncols ? $cols[$l]: undef;
+	$cost = ((defined $row and defined $col and defined $cost{$row}{$col}) ?
+		 $cost{$row}{$col} : $no_match_cost) - $col_min[$l];
+	if (($l<0) or ($cost != ($row_dec[$k] - $col_inc[$l]))) {
+	    next unless $l<0 or abs($cost - ($row_dec[$k] - $col_inc[$l])) > $required_precision*max(abs($row_dec[$k]),abs($col_inc[$l]));
+	    warn "BGM: every row should have a column mate: row $row doesn't, col: $col\n";
+	    return undef;
+	}
+    }
+
+    my %map;
+    for ($l=0; $l<@row_mate; $l++) {
+	$k = $row_mate[$l];
+	$row = $k < $nrows ? $rows[$k] : undef;
+	$col = $l < $ncols ? $cols[$l]: undef;
+	next unless defined $row and defined $col and defined $cost{$row}{$col};
+	$reverse_search ? ($map{$col} = $row) : ($map{$row} = $col);
+    }
+    return {%map};
+}
\ No newline at end of file

From 9de5ad63f9d03e04deae7f114d00b0703ba4e42c Mon Sep 17 00:00:00 2001
From: qingen <qingenz123@126.com>
Date: Fri, 14 Jan 2022 19:54:47 +0800
Subject: [PATCH 3/9] [vector] add AMI data preparation scripts

---
 dataset/ami/.gitignore     |   1 +
 dataset/ami/README.md      |   5 +
 dataset/ami/ami_prepare.py | 602 +++++++++++++++++++++++++++++++++++++
 dataset/ami/ami_splits.py  | 252 ++++++++++++++++
 utils/dataio.py            |  82 +++++
 5 files changed, 942 insertions(+)
 create mode 100644 dataset/ami/.gitignore
 create mode 100644 dataset/ami/README.md
 create mode 100644 dataset/ami/ami_prepare.py
 create mode 100644 dataset/ami/ami_splits.py
 create mode 100644 utils/dataio.py

diff --git a/dataset/ami/.gitignore b/dataset/ami/.gitignore
new file mode 100644
index 000000000..872aa273a
--- /dev/null
+++ b/dataset/ami/.gitignore
@@ -0,0 +1 @@
+results
\ No newline at end of file
diff --git a/dataset/ami/README.md b/dataset/ami/README.md
new file mode 100644
index 000000000..ac65eedf6
--- /dev/null
+++ b/dataset/ami/README.md
@@ -0,0 +1,5 @@
+# [AMI](https://groups.inf.ed.ac.uk/ami/corpus/)
+
+The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings. For a gentle introduction to the corpus, see the [corpus overview](https://groups.inf.ed.ac.uk/ami/corpus/overview.shtml). To access the data, follow the directions given [there](https://groups.inf.ed.ac.uk/ami/download). Around two-thirds of the data has been elicited using a scenario in which the participants play different roles in a design team, taking a design project from kick-off to completion over the course of a day. The rest consists of naturally occurring meetings in a range of domains. 
+
+Detailed information can be found in the [documentation section](http://groups.inf.ed.ac.uk/ami/corpus/datasets.shtml).
diff --git a/dataset/ami/ami_prepare.py b/dataset/ami/ami_prepare.py
new file mode 100644
index 000000000..8c0fc62dc
--- /dev/null
+++ b/dataset/ami/ami_prepare.py
@@ -0,0 +1,602 @@
+"""
+Data preparation.
+
+Download: http://groups.inf.ed.ac.uk/ami/download/
+
+Prepares metadata files (JSON) from manual annotations "segments/" using RTTM format (Oracle VAD).
+
+Authors
+ * qingenz123@126.com (Qingen ZHAO) 2022
+
+"""
+
+import os
+import logging
+import argparse
+import xml.etree.ElementTree as et
+import glob
+import json
+from ami_splits import get_AMI_split
+from distutils.util import strtobool
+
+from utils.dataio import (
+    load_pkl,
+    save_pkl,
+)
+
+logger = logging.getLogger(__name__)
+SAMPLERATE = 16000
+
+
+def prepare_ami(
+    data_folder,
+    manual_annot_folder,
+    save_folder,
+    ref_rttm_dir,
+    meta_data_dir,
+    split_type="full_corpus_asr",
+    skip_TNO=True,
+    mic_type="Mix-Headset",
+    vad_type="oracle",
+    max_subseg_dur=3.0,
+    overlap=1.5,
+):
+    """
+    Prepares reference RTTM and JSON files for the AMI dataset.
+
+    Arguments
+    ---------
+    data_folder : str
+        Path to the folder where the original amicorpus is stored.
+    manual_annot_folder : str
+        Directory where the manual annotations are stored.
+    save_folder : str
+        The save directory in results.
+    ref_rttm_dir : str
+        Directory to store reference RTTM files.
+    meta_data_dir : str
+        Directory to store the meta data (json) files.
+    split_type : str
+        Standard dataset split. See ami_splits.py for more information.
+        Allowed split_type: "scenario_only", "full_corpus" or "full_corpus_asr"
+    skip_TNO: bool
+        Skips TNO meeting recordings if True.
+    mic_type : str
+        Type of microphone to be used.
+    vad_type : str
+        Type of VAD. Kept for future when VAD will be added.
+    max_subseg_dur : float
+        Duration in seconds of a subsegments to be prepared from larger segments.
+    overlap : float
+        Overlap duration in seconds between adjacent subsegments
+
+    Example
+    -------
+    >>> from recipes.AMI.ami_prepare import prepare_ami
+    >>> data_folder = '/network/datasets/ami/amicorpus/'
+    >>> manual_annot_folder = '/home/mila/d/dawalatn/nauman/ami_public_manual/'
+    >>> save_folder = 'results/save/'
+    >>> split_type = 'full_corpus_asr'
+    >>> mic_type = 'Lapel'
+    >>> prepare_ami(data_folder, manual_annot_folder, save_folder, split_type, mic_type)
+    """
+
+    # Meta files
+    meta_files = [
+        os.path.join(meta_data_dir, "ami_train." + mic_type + ".subsegs.json"),
+        os.path.join(meta_data_dir, "ami_dev." + mic_type + ".subsegs.json"),
+        os.path.join(meta_data_dir, "ami_eval." + mic_type + ".subsegs.json"),
+    ]
+
+    # Create configuration for easily skipping data_preparation stage
+    conf = {
+        "data_folder": data_folder,
+        "save_folder": save_folder,
+        "ref_rttm_dir": ref_rttm_dir,
+        "meta_data_dir": meta_data_dir,
+        "split_type": split_type,
+        "skip_TNO": skip_TNO,
+        "mic_type": mic_type,
+        "vad": vad_type,
+        "max_subseg_dur": max_subseg_dur,
+        "overlap": overlap,
+        "meta_files": meta_files,
+    }
+
+    if not os.path.exists(save_folder):
+        os.makedirs(save_folder)
+
+    # Setting output option files.
+    opt_file = "opt_ami_prepare." + mic_type + ".pkl"
+
+    # Check if this phase is already done (if so, skip it)
+    if skip(save_folder, conf, meta_files, opt_file):
+        logger.info(
+            "Skipping data preparation, as it was completed in previous run."
+        )
+        return
+
+    msg = "\tCreating meta-data file for the AMI Dataset.."
+    logger.debug(msg)
+
+    # Get the split
+    train_set, dev_set, eval_set = get_AMI_split(split_type)
+
+    # Prepare RTTM from XML(manual annot) and store are groundtruth
+    # Create ref_RTTM directory
+    if not os.path.exists(ref_rttm_dir):
+        os.makedirs(ref_rttm_dir)
+
+    # Create reference RTTM files
+    splits = ["train", "dev", "eval"]
+    for i in splits:
+        rttm_file = ref_rttm_dir + "/fullref_ami_" + i + ".rttm"
+        if i == "train":
+            prepare_segs_for_RTTM(
+                train_set,
+                rttm_file,
+                data_folder,
+                manual_annot_folder,
+                i,
+                skip_TNO,
+            )
+        if i == "dev":
+            prepare_segs_for_RTTM(
+                dev_set,
+                rttm_file,
+                data_folder,
+                manual_annot_folder,
+                i,
+                skip_TNO,
+            )
+        if i == "eval":
+            prepare_segs_for_RTTM(
+                eval_set,
+                rttm_file,
+                data_folder,
+                manual_annot_folder,
+                i,
+                skip_TNO,
+            )
+
+    # Create meta_files for splits
+    meta_data_dir = meta_data_dir
+    if not os.path.exists(meta_data_dir):
+        os.makedirs(meta_data_dir)
+
+    for i in splits:
+        rttm_file = ref_rttm_dir + "/fullref_ami_" + i + ".rttm"
+        meta_filename_prefix = "ami_" + i
+        prepare_metadata(
+            rttm_file,
+            meta_data_dir,
+            data_folder,
+            meta_filename_prefix,
+            max_subseg_dur,
+            overlap,
+            mic_type,
+        )
+
+    save_opt_file = os.path.join(save_folder, opt_file)
+    save_pkl(conf, save_opt_file)
+
+
+def get_RTTM_per_rec(segs, spkrs_list, rec_id):
+    """Prepares rttm for each recording
+    """
+
+    rttm = []
+
+    # Prepare header
+    for spkr_id in spkrs_list:
+        # e.g. SPKR-INFO ES2008c 0 <NA> <NA> <NA> unknown ES2008c.A_PM <NA> <NA>
+        line = (
+            "SPKR-INFO "
+            + rec_id
+            + " 0 <NA> <NA> <NA> unknown "
+            + spkr_id
+            + " <NA> <NA>"
+        )
+        rttm.append(line)
+
+    # Append remaining lines
+    for row in segs:
+        # e.g. SPEAKER ES2008c 0 37.880 0.590 <NA> <NA> ES2008c.A_PM <NA> <NA>
+
+        if float(row[1]) < float(row[0]):
+            msg1 = (
+                "Possibly Incorrect Annotation Found!! transcriber_start (%s) > transcriber_end (%s)"
+                % (row[0], row[1])
+            )
+            msg2 = (
+                "Excluding this incorrect row from the RTTM : %s, %s, %s, %s"
+                % (
+                    rec_id,
+                    row[0],
+                    str(round(float(row[1]) - float(row[0]), 4)),
+                    str(row[2]),
+                )
+            )
+            logger.info(msg1)
+            logger.info(msg2)
+            continue
+
+        line = (
+            "SPEAKER "
+            + rec_id
+            + " 0 "
+            + str(round(float(row[0]), 4))
+            + " "
+            + str(round(float(row[1]) - float(row[0]), 4))
+            + " <NA> <NA> "
+            + str(row[2])
+            + " <NA> <NA>"
+        )
+        rttm.append(line)
+
+    return rttm
+
+
+def prepare_segs_for_RTTM(
+    list_ids, out_rttm_file, audio_dir, annot_dir, split_type, skip_TNO
+):
+
+    RTTM = []  # Stores all RTTMs clubbed together for a given dataset split
+
+    for main_meet_id in list_ids:
+
+        # Skip TNO meetings from dev and eval sets
+        if (
+            main_meet_id.startswith("TS")
+            and split_type != "train"
+            and skip_TNO is True
+        ):
+            msg = (
+                "Skipping TNO meeting in AMI "
+                + str(split_type)
+                + " set : "
+                + str(main_meet_id)
+            )
+            logger.info(msg)
+            continue
+
+        list_sessions = glob.glob(audio_dir + "/" + main_meet_id + "*")
+        list_sessions.sort()
+
+        for sess in list_sessions:
+            rec_id = os.path.basename(sess)
+            path = annot_dir + "/segments/" + rec_id
+            f = path + ".*.segments.xml"
+            list_spkr_xmls = glob.glob(f)
+            list_spkr_xmls.sort()  # A, B, C, D, E etc (Speakers)
+            segs = []
+            spkrs_list = (
+                []
+            )  # Since non-scenario recordings contains 3-5 speakers
+
+            for spkr_xml_file in list_spkr_xmls:
+
+                # Speaker ID
+                spkr = os.path.basename(spkr_xml_file).split(".")[1]
+                spkr_ID = rec_id + "." + spkr
+                spkrs_list.append(spkr_ID)
+
+                # Parse xml tree
+                tree = et.parse(spkr_xml_file)
+                root = tree.getroot()
+
+                # Start, end and speaker_ID from xml file
+                segs = segs + [
+                    [
+                        elem.attrib["transcriber_start"],
+                        elem.attrib["transcriber_end"],
+                        spkr_ID,
+                    ]
+                    for elem in root.iter("segment")
+                ]
+
+            # Sort rows as per the start time (per recording)
+            segs.sort(key=lambda x: float(x[0]))
+
+            rttm_per_rec = get_RTTM_per_rec(segs, spkrs_list, rec_id)
+            RTTM = RTTM + rttm_per_rec
+
+    # Write one RTTM as groundtruth. For example, "fullref_eval.rttm"
+    with open(out_rttm_file, "w") as f:
+        for item in RTTM:
+            f.write("%s\n" % item)
+
+
+def is_overlapped(end1, start2):
+    """Returns True if the two segments overlap
+
+    Arguments
+    ---------
+    end1 : float
+        End time of the first segment.
+    start2 : float
+        Start time of the second segment.
+    """
+
+    if start2 > end1:
+        return False
+    else:
+        return True
+
+
+def merge_rttm_intervals(rttm_segs):
+    """Merges adjacent segments in rttm if they overlap.
+    """
+    # For one recording
+    # rec_id = rttm_segs[0][1]
+    rttm_segs.sort(key=lambda x: float(x[3]))
+
+    # first_seg = rttm_segs[0] # first interval.. as it is
+    merged_segs = [rttm_segs[0]]
+    strt = float(rttm_segs[0][3])
+    end = float(rttm_segs[0][3]) + float(rttm_segs[0][4])
+
+    for row in rttm_segs[1:]:
+        s = float(row[3])
+        e = float(row[3]) + float(row[4])
+
+        if is_overlapped(end, s):
+            # Update only end. The strt will be same as in last segment
+            # Just update last row in the merged_segs
+            end = max(end, e)
+            merged_segs[-1][3] = str(round(strt, 4))
+            merged_segs[-1][4] = str(round((end - strt), 4))
+            merged_segs[-1][7] = "overlap"  # previous_row[7] + '-'+ row[7]
+        else:
+            # Add a new disjoint segment
+            strt = s
+            end = e
+            merged_segs.append(row)  # this will have 1 spkr ID
+
+    return merged_segs
+
+
+def get_subsegments(merged_segs, max_subseg_dur=3.0, overlap=1.5):
+    """Divides bigger segments into smaller sub-segments
+    """
+
+    shift = max_subseg_dur - overlap
+    subsegments = []
+
+    # These rows are in RTTM format
+    for row in merged_segs:
+        seg_dur = float(row[4])
+        rec_id = row[1]
+
+        if seg_dur > max_subseg_dur:
+            num_subsegs = int(seg_dur / shift)
+            # Taking 0.01 sec as small step
+            seg_start = float(row[3])
+            seg_end = seg_start + seg_dur
+
+            # Now divide this segment (new_row) in smaller subsegments
+            for i in range(num_subsegs):
+                subseg_start = seg_start + i * shift
+                subseg_end = min(subseg_start + max_subseg_dur - 0.01, seg_end)
+                subseg_dur = subseg_end - subseg_start
+
+                new_row = [
+                    "SPEAKER",
+                    rec_id,
+                    "0",
+                    str(round(float(subseg_start), 4)),
+                    str(round(float(subseg_dur), 4)),
+                    "<NA>",
+                    "<NA>",
+                    row[7],
+                    "<NA>",
+                    "<NA>",
+                ]
+
+                subsegments.append(new_row)
+
+                # Break if exceeding the boundary
+                if subseg_end >= seg_end:
+                    break
+        else:
+            subsegments.append(row)
+
+    return subsegments
+
+
+def prepare_metadata(
+    rttm_file, save_dir, data_dir, filename, max_subseg_dur, overlap, mic_type
+):
+    # Read RTTM, get unique meeting_IDs (from RTTM headers)
+    # For each MeetingID. select that meetID -> merge -> subsegment -> json -> append
+
+    # Read RTTM
+    RTTM = []
+    with open(rttm_file, "r") as f:
+        for line in f:
+            entry = line[:-1]
+            RTTM.append(entry)
+
+    spkr_info = filter(lambda x: x.startswith("SPKR-INFO"), RTTM)
+    rec_ids = list(set([row.split(" ")[1] for row in spkr_info]))
+    rec_ids.sort()  # sorting just to make JSON look in proper sequence
+
+    # For each recording merge segments and then perform subsegmentation
+    MERGED_SEGMENTS = []
+    SUBSEGMENTS = []
+    for rec_id in rec_ids:
+        segs_iter = filter(
+            lambda x: x.startswith("SPEAKER " + str(rec_id)), RTTM
+        )
+        gt_rttm_segs = [row.split(" ") for row in segs_iter]
+
+        # Merge, subsegment and then convert to json format.
+        merged_segs = merge_rttm_intervals(
+            gt_rttm_segs
+        )  # We lose speaker_ID after merging
+        MERGED_SEGMENTS = MERGED_SEGMENTS + merged_segs
+
+        # Divide segments into smaller sub-segments
+        subsegs = get_subsegments(merged_segs, max_subseg_dur, overlap)
+        SUBSEGMENTS = SUBSEGMENTS + subsegs
+
+    # Write segment AND sub-segments (in RTTM format)
+    segs_file = save_dir + "/" + filename + ".segments.rttm"
+    subsegment_file = save_dir + "/" + filename + ".subsegments.rttm"
+
+    with open(segs_file, "w") as f:
+        for row in MERGED_SEGMENTS:
+            line_str = " ".join(row)
+            f.write("%s\n" % line_str)
+
+    with open(subsegment_file, "w") as f:
+        for row in SUBSEGMENTS:
+            line_str = " ".join(row)
+            f.write("%s\n" % line_str)
+
+    # Create JSON from subsegments
+    json_dict = {}
+    for row in SUBSEGMENTS:
+        rec_id = row[1]
+        strt = str(round(float(row[3]), 4))
+        end = str(round((float(row[3]) + float(row[4])), 4))
+        subsegment_ID = rec_id + "_" + strt + "_" + end
+        dur = row[4]
+        start_sample = int(float(strt) * SAMPLERATE)
+        end_sample = int(float(end) * SAMPLERATE)
+
+        # If multi-mic audio is selected
+        if mic_type == "Array1":
+            wav_file_base_path = (
+                data_dir
+                + "/"
+                + rec_id
+                + "/audio/"
+                + rec_id
+                + "."
+                + mic_type
+                + "-"
+            )
+
+            f = []  # adding all 8 mics
+            for i in range(8):
+                f.append(wav_file_base_path + str(i + 1).zfill(2) + ".wav")
+            audio_files_path_list = f
+
+            # Note: key "files" with 's' is used for multi-mic
+            json_dict[subsegment_ID] = {
+                "wav": {
+                    "files": audio_files_path_list,
+                    "duration": float(dur),
+                    "start": int(start_sample),
+                    "stop": int(end_sample),
+                },
+            }
+        else:
+            # Single mic audio
+            wav_file_path = (
+                data_dir
+                + "/"
+                + rec_id
+                + "/audio/"
+                + rec_id
+                + "."
+                + mic_type
+                + ".wav"
+            )
+
+            # Note: key "file" without 's' is used for single-mic
+            json_dict[subsegment_ID] = {
+                "wav": {
+                    "file": wav_file_path,
+                    "duration": float(dur),
+                    "start": int(start_sample),
+                    "stop": int(end_sample),
+                },
+            }
+
+    out_json_file = save_dir + "/" + filename + "." + mic_type + ".subsegs.json"
+    with open(out_json_file, mode="w") as json_f:
+        json.dump(json_dict, json_f, indent=2)
+
+    msg = "%s JSON prepared" % (out_json_file)
+    logger.debug(msg)
+
+
+def skip(save_folder, conf, meta_files, opt_file):
+    """
+    Detects if the AMI data_preparation has been already done.
+    If the preparation has been done, we can skip it.
+
+    Returns
+    -------
+    bool
+        if True, the preparation phase can be skipped.
+        if False, it must be done.
+    """
+    # Checking if meta (json) files are available
+    skip = True
+    for file_path in meta_files:
+        if not os.path.isfile(file_path):
+            skip = False
+
+    # Checking saved options
+    save_opt_file = os.path.join(save_folder, opt_file)
+    if skip is True:
+        if os.path.isfile(save_opt_file):
+            opts_old = load_pkl(save_opt_file)
+            if opts_old == conf:
+                skip = True
+            else:
+                skip = False
+        else:
+            skip = False
+
+    return skip
+
+if __name__ == '__main__':
+
+    parser = argparse.ArgumentParser(
+        prog='python ami_prepare.py  --data_folder /home/data/ami/amicorpus \
+            --manual_annot_folder /home/data/ami/ami_public_manual_1.6.2 \
+            --save_folder ./results/ --ref_rttm_dir ./results/ref_rttms \
+            --meta_data_dir ./results/metadata',
+        description='AMI Data preparation') 
+    parser.add_argument(
+        '--data_folder', required=True, help='Path to the folder where the original amicorpus is stored')
+    parser.add_argument(
+        '--manual_annot_folder', required=True, help='Directory where the manual annotations are stored')
+    parser.add_argument(
+        '--save_folder', required=True, help='The save directory in results')
+    parser.add_argument(
+        '--ref_rttm_dir', required=True, help='Directory to store reference RTTM files')
+    parser.add_argument(
+        '--meta_data_dir', required=True, help='Directory to store the meta data (json) files')
+    parser.add_argument(
+        '--split_type', 
+        default="full_corpus_asr", 
+        help='Standard dataset split. See ami_splits.py for more information')
+    parser.add_argument(
+        '--skip_TNO', default=True, type=strtobool, help='Skips TNO meeting recordings if True')
+    parser.add_argument(
+        '--mic_type', default="Mix-Headset", help='Type of microphone to be used')
+    parser.add_argument(
+        '--vad_type', default="oracle", help='Type of VAD. Kept for future when VAD will be added')
+    parser.add_argument(
+        '--max_subseg_dur', 
+        default=3.0, 
+        type=float, 
+        help='Duration in seconds of a subsegments to be prepared from larger segments')
+    parser.add_argument(
+        '--overlap', default=1.5, type=float, help='Overlap duration in seconds between adjacent subsegments')
+
+    args = parser.parse_args()
+    print(args)
+
+    prepare_ami(
+        args.data_folder, 
+        args.manual_annot_folder, 
+        args.save_folder, 
+        args.ref_rttm_dir, 
+        args.meta_data_dir
+        )
\ No newline at end of file
diff --git a/dataset/ami/ami_splits.py b/dataset/ami/ami_splits.py
new file mode 100644
index 000000000..dd8410df8
--- /dev/null
+++ b/dataset/ami/ami_splits.py
@@ -0,0 +1,252 @@
+"""
+AMI corpus contained 100 hours of meeting recording.
+This script returns the standard train, dev and eval split for AMI corpus.
+For more information on dataset please refer to http://groups.inf.ed.ac.uk/ami/corpus/datasets.shtml
+
+Authors
+ * qingenz123@126.com (Qingen ZHAO) 2022
+
+Credits
+
+"""
+
+ALLOWED_OPTIONS = ["scenario_only", "full_corpus", "full_corpus_asr"]
+
+
+def get_AMI_split(split_option):
+    """
+    Prepares train, dev, and test sets for given split_option
+
+    Arguments
+    ---------
+    split_option: str
+        The standard split option.
+        Allowed options: "scenario_only", "full_corpus", "full_corpus_asr"
+
+    Returns
+    -------
+        Meeting IDs for train, dev, and test sets for given split_option
+    """
+
+    if split_option not in ALLOWED_OPTIONS:
+        print(
+            f'Invalid split "{split_option}" requested!\nValid split_options are: ',
+            ALLOWED_OPTIONS,
+        )
+        return
+
+    if split_option == "scenario_only":
+
+        train_set = [
+            "ES2002",
+            "ES2005",
+            "ES2006",
+            "ES2007",
+            "ES2008",
+            "ES2009",
+            "ES2010",
+            "ES2012",
+            "ES2013",
+            "ES2015",
+            "ES2016",
+            "IS1000",
+            "IS1001",
+            "IS1002",
+            "IS1003",
+            "IS1004",
+            "IS1005",
+            "IS1006",
+            "IS1007",
+            "TS3005",
+            "TS3008",
+            "TS3009",
+            "TS3010",
+            "TS3011",
+            "TS3012",
+        ]
+
+        dev_set = [
+            "ES2003",
+            "ES2011",
+            "IS1008",
+            "TS3004",
+            "TS3006",
+        ]
+
+        test_set = [
+            "ES2004",
+            "ES2014",
+            "IS1009",
+            "TS3003",
+            "TS3007",
+        ]
+
+    if split_option == "full_corpus":
+        # List of train: SA (TRAINING PART OF SEEN DATA)
+        train_set = [
+            "ES2002",
+            "ES2005",
+            "ES2006",
+            "ES2007",
+            "ES2008",
+            "ES2009",
+            "ES2010",
+            "ES2012",
+            "ES2013",
+            "ES2015",
+            "ES2016",
+            "IS1000",
+            "IS1001",
+            "IS1002",
+            "IS1003",
+            "IS1004",
+            "IS1005",
+            "IS1006",
+            "IS1007",
+            "TS3005",
+            "TS3008",
+            "TS3009",
+            "TS3010",
+            "TS3011",
+            "TS3012",
+            "EN2001",
+            "EN2003",
+            "EN2004",
+            "EN2005",
+            "EN2006",
+            "EN2009",
+            "IN1001",
+            "IN1002",
+            "IN1005",
+            "IN1007",
+            "IN1008",
+            "IN1009",
+            "IN1012",
+            "IN1013",
+            "IN1014",
+            "IN1016",
+        ]
+
+        # List of dev: SB (DEV PART OF SEEN DATA)
+        dev_set = [
+            "ES2003",
+            "ES2011",
+            "IS1008",
+            "TS3004",
+            "TS3006",
+            "IB4001",
+            "IB4002",
+            "IB4003",
+            "IB4004",
+            "IB4010",
+            "IB4011",
+        ]
+
+        # List of test: SC (UNSEEN DATA FOR EVALUATION)
+        # Note that IB4005 does not appear because it has speakers in common with two sets of data.
+        test_set = [
+            "ES2004",
+            "ES2014",
+            "IS1009",
+            "TS3003",
+            "TS3007",
+            "EN2002",
+        ]
+
+    if split_option == "full_corpus_asr":
+        train_set = [
+            "ES2002",
+            "ES2003",
+            "ES2005",
+            "ES2006",
+            "ES2007",
+            "ES2008",
+            "ES2009",
+            "ES2010",
+            "ES2012",
+            "ES2013",
+            "ES2014",
+            "ES2015",
+            "ES2016",
+            "IS1000",
+            "IS1001",
+            "IS1002",
+            "IS1003",
+            "IS1004",
+            "IS1005",
+            "IS1006",
+            "IS1007",
+            "TS3005",
+            "TS3006",
+            "TS3007",
+            "TS3008",
+            "TS3009",
+            "TS3010",
+            "TS3011",
+            "TS3012",
+            "EN2001",
+            "EN2003",
+            "EN2004",
+            "EN2005",
+            "EN2006",
+            "EN2009",
+            "IN1001",
+            "IN1002",
+            "IN1005",
+            "IN1007",
+            "IN1008",
+            "IN1009",
+            "IN1012",
+            "IN1013",
+            "IN1014",
+            "IN1016",
+        ]
+
+        dev_set0 = [
+            "ES2011",
+            "IS1008",
+            "TS3004",
+            "IB4001",
+            "IB4002",
+            "IB4003",
+            "IB4004",
+            "IB4010",
+            "IB4011",
+        ]
+
+        test_set0 = [
+            "ES2004",
+            "IS1009",
+            "TS3003",
+            "EN2002",
+        ]
+
+        dev_set1 = [
+            "ES2011a",
+            "IS1008a",
+            "TS3004a",
+            "IB4001",
+            "IB4002",
+            "IB4003",
+            "IB4004",            
+        ]
+        test_set1 = [
+            "ES2004a",
+            "IS1009a",
+            "TS3003a",
+            "EN2001a",
+        ]
+
+        train_set = [
+            "IB4001",
+            "IB4002",
+            "IB4003",
+            "IB4004",
+        ]
+        dev_set = [
+            "IB4002",
+        ]
+        test_set = [
+            "IB4004", 
+        ]
+    return train_set, dev_set, test_set
diff --git a/utils/dataio.py b/utils/dataio.py
new file mode 100644
index 000000000..48f792052
--- /dev/null
+++ b/utils/dataio.py
@@ -0,0 +1,82 @@
+"""
+Data reading and writing.
+
+Authors
+ * qingenz123@126.com (Qingen ZHAO) 2022
+ 
+"""
+
+import os
+import pickle
+
+def save_pkl(obj, file):
+    """Save an object in pkl format.
+
+    Arguments
+    ---------
+    obj : object
+        Object to save in pkl format
+    file : str
+        Path to the output file
+    sampling_rate : int
+        Sampling rate of the audio file, TODO: this is not used?
+
+    Example
+    -------
+    >>> tmpfile = os.path.join(getfixture('tmpdir'), "example.pkl")
+    >>> save_pkl([1, 2, 3, 4, 5], tmpfile)
+    >>> load_pkl(tmpfile)
+    [1, 2, 3, 4, 5]
+    """
+    with open(file, "wb") as f:
+        pickle.dump(obj, f)
+
+def load_pickle(pickle_path):
+    """Utility function for loading .pkl pickle files.
+
+    Arguments
+    ---------
+    pickle_path : str
+        Path to pickle file.
+
+    Returns
+    -------
+    out : object
+        Python object loaded from pickle.
+    """
+    with open(pickle_path, "rb") as f:
+        out = pickle.load(f)
+    return out
+
+def load_pkl(file):
+    """Loads a pkl file.
+
+    For an example, see `save_pkl`.
+
+    Arguments
+    ---------
+    file : str
+        Path to the input pkl file.
+
+    Returns
+    -------
+    The loaded object.
+    """
+
+    # Deals with the situation where two processes are trying
+    # to access the same label dictionary by creating a lock
+    count = 100
+    while count > 0:
+        if os.path.isfile(file + ".lock"):
+            time.sleep(1)
+            count -= 1
+        else:
+            break
+
+    try:
+        open(file + ".lock", "w").close()
+        with open(file, "rb") as f:
+            return pickle.load(f)
+    finally:
+        if os.path.isfile(file + ".lock"):
+            os.remove(file + ".lock")
\ No newline at end of file

From 98788ca27e70194a477ccad3088fb171dfa5e2a4 Mon Sep 17 00:00:00 2001
From: qingen <qingenz123@126.com>
Date: Fri, 14 Jan 2022 20:03:19 +0800
Subject: [PATCH 4/9] [vector] add AMI data preparation scripts

---
 dataset/ami/ami_splits.py | 34 ++--------------------------------
 utils/DER.py              |  2 +-
 2 files changed, 3 insertions(+), 33 deletions(-)

diff --git a/dataset/ami/ami_splits.py b/dataset/ami/ami_splits.py
index dd8410df8..52a8ddc04 100644
--- a/dataset/ami/ami_splits.py
+++ b/dataset/ami/ami_splits.py
@@ -6,8 +6,6 @@ For more information on dataset please refer to http://groups.inf.ed.ac.uk/ami/c
 Authors
  * qingenz123@126.com (Qingen ZHAO) 2022
 
-Credits
-
 """
 
 ALLOWED_OPTIONS = ["scenario_only", "full_corpus", "full_corpus_asr"]
@@ -202,7 +200,7 @@ def get_AMI_split(split_option):
             "IN1016",
         ]
 
-        dev_set0 = [
+        dev_set = [
             "ES2011",
             "IS1008",
             "TS3004",
@@ -214,39 +212,11 @@ def get_AMI_split(split_option):
             "IB4011",
         ]
 
-        test_set0 = [
+        test_set = [
             "ES2004",
             "IS1009",
             "TS3003",
             "EN2002",
         ]
 
-        dev_set1 = [
-            "ES2011a",
-            "IS1008a",
-            "TS3004a",
-            "IB4001",
-            "IB4002",
-            "IB4003",
-            "IB4004",            
-        ]
-        test_set1 = [
-            "ES2004a",
-            "IS1009a",
-            "TS3003a",
-            "EN2001a",
-        ]
-
-        train_set = [
-            "IB4001",
-            "IB4002",
-            "IB4003",
-            "IB4004",
-        ]
-        dev_set = [
-            "IB4002",
-        ]
-        test_set = [
-            "IB4004", 
-        ]
     return train_set, dev_set, test_set
diff --git a/utils/DER.py b/utils/DER.py
index 25003b0a4..11dfa8cfa 100755
--- a/utils/DER.py
+++ b/utils/DER.py
@@ -4,7 +4,7 @@ False Alarm (FA), and Speaker Error Rate (SER) using md-eval-22.pl from NIST RT
 Authors
  * Neville Ryant 2018
  * Nauman Dawalatabad 2020
- * Qingen Zhao 2021
+ * qingenz123@126.com (Qingen ZHAO) 2022
 
 Credits
  This code is adapted from https://github.com/nryant/dscore

From 14d9e80b0d5f4b1620356231de7b21090090aae8 Mon Sep 17 00:00:00 2001
From: qingen <qingenz123@126.com>
Date: Tue, 18 Jan 2022 09:47:51 +0800
Subject: [PATCH 5/9] [vector] add AMI data preparation scripts

---
 dataset/ami/ami_prepare.py                    | 233 ++++++++----------
 dataset/ami/ami_splits.py                     |  16 +-
 {utils => dataset/ami}/dataio.py              |  19 +-
 {utils => paddlespeech/vector/utils}/DER.py   |  55 +++--
 .../vector/utils}/md-eval.pl                  |   0
 5 files changed, 167 insertions(+), 156 deletions(-)
 rename {utils => dataset/ami}/dataio.py (71%)
 rename {utils => paddlespeech/vector/utils}/DER.py (80%)
 rename {utils => paddlespeech/vector/utils}/md-eval.pl (100%)

diff --git a/dataset/ami/ami_prepare.py b/dataset/ami/ami_prepare.py
index 8c0fc62dc..44993cead 100644
--- a/dataset/ami/ami_prepare.py
+++ b/dataset/ami/ami_prepare.py
@@ -1,3 +1,16 @@
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 """
 Data preparation.
 
@@ -21,26 +34,24 @@ from distutils.util import strtobool
 
 from utils.dataio import (
     load_pkl,
-    save_pkl,
-)
+    save_pkl, )
 
 logger = logging.getLogger(__name__)
 SAMPLERATE = 16000
 
 
 def prepare_ami(
-    data_folder,
-    manual_annot_folder,
-    save_folder,
-    ref_rttm_dir,
-    meta_data_dir,
-    split_type="full_corpus_asr",
-    skip_TNO=True,
-    mic_type="Mix-Headset",
-    vad_type="oracle",
-    max_subseg_dur=3.0,
-    overlap=1.5,
-):
+        data_folder,
+        manual_annot_folder,
+        save_folder,
+        ref_rttm_dir,
+        meta_data_dir,
+        split_type="full_corpus_asr",
+        skip_TNO=True,
+        mic_type="Mix-Headset",
+        vad_type="oracle",
+        max_subseg_dur=3.0,
+        overlap=1.5, ):
     """
     Prepares reference RTTM and JSON files for the AMI dataset.
 
@@ -72,12 +83,12 @@ def prepare_ami(
 
     Example
     -------
-    >>> from recipes.AMI.ami_prepare import prepare_ami
-    >>> data_folder = '/network/datasets/ami/amicorpus/'
-    >>> manual_annot_folder = '/home/mila/d/dawalatn/nauman/ami_public_manual/'
-    >>> save_folder = 'results/save/'
+    >>> from dataset.ami.ami_prepare import prepare_ami
+    >>> data_folder = '/home/data/ami/amicorpus/'
+    >>> manual_annot_folder = '/home/data/ami/ami_public_manual/'
+    >>> save_folder = './results/
     >>> split_type = 'full_corpus_asr'
-    >>> mic_type = 'Lapel'
+    >>> mic_type = 'Mix-Headset'
     >>> prepare_ami(data_folder, manual_annot_folder, save_folder, split_type, mic_type)
     """
 
@@ -112,8 +123,7 @@ def prepare_ami(
     # Check if this phase is already done (if so, skip it)
     if skip(save_folder, conf, meta_files, opt_file):
         logger.info(
-            "Skipping data preparation, as it was completed in previous run."
-        )
+            "Skipping data preparation, as it was completed in previous run.")
         return
 
     msg = "\tCreating meta-data file for the AMI Dataset.."
@@ -138,8 +148,7 @@ def prepare_ami(
                 data_folder,
                 manual_annot_folder,
                 i,
-                skip_TNO,
-            )
+                skip_TNO, )
         if i == "dev":
             prepare_segs_for_RTTM(
                 dev_set,
@@ -147,8 +156,7 @@ def prepare_ami(
                 data_folder,
                 manual_annot_folder,
                 i,
-                skip_TNO,
-            )
+                skip_TNO, )
         if i == "eval":
             prepare_segs_for_RTTM(
                 eval_set,
@@ -156,8 +164,7 @@ def prepare_ami(
                 data_folder,
                 manual_annot_folder,
                 i,
-                skip_TNO,
-            )
+                skip_TNO, )
 
     # Create meta_files for splits
     meta_data_dir = meta_data_dir
@@ -174,8 +181,7 @@ def prepare_ami(
             meta_filename_prefix,
             max_subseg_dur,
             overlap,
-            mic_type,
-        )
+            mic_type, )
 
     save_opt_file = os.path.join(save_folder, opt_file)
     save_pkl(conf, save_opt_file)
@@ -190,13 +196,8 @@ def get_RTTM_per_rec(segs, spkrs_list, rec_id):
     # Prepare header
     for spkr_id in spkrs_list:
         # e.g. SPKR-INFO ES2008c 0 <NA> <NA> <NA> unknown ES2008c.A_PM <NA> <NA>
-        line = (
-            "SPKR-INFO "
-            + rec_id
-            + " 0 <NA> <NA> <NA> unknown "
-            + spkr_id
-            + " <NA> <NA>"
-        )
+        line = ("SPKR-INFO " + rec_id + " 0 <NA> <NA> <NA> unknown " + spkr_id +
+                " <NA> <NA>")
         rttm.append(line)
 
     # Append remaining lines
@@ -206,57 +207,35 @@ def get_RTTM_per_rec(segs, spkrs_list, rec_id):
         if float(row[1]) < float(row[0]):
             msg1 = (
                 "Possibly Incorrect Annotation Found!! transcriber_start (%s) > transcriber_end (%s)"
-                % (row[0], row[1])
-            )
+                % (row[0], row[1]))
             msg2 = (
-                "Excluding this incorrect row from the RTTM : %s, %s, %s, %s"
-                % (
-                    rec_id,
-                    row[0],
-                    str(round(float(row[1]) - float(row[0]), 4)),
-                    str(row[2]),
-                )
-            )
+                "Excluding this incorrect row from the RTTM : %s, %s, %s, %s" %
+                (rec_id, row[0], str(round(float(row[1]) - float(row[0]), 4)),
+                 str(row[2]), ))
             logger.info(msg1)
             logger.info(msg2)
             continue
 
-        line = (
-            "SPEAKER "
-            + rec_id
-            + " 0 "
-            + str(round(float(row[0]), 4))
-            + " "
-            + str(round(float(row[1]) - float(row[0]), 4))
-            + " <NA> <NA> "
-            + str(row[2])
-            + " <NA> <NA>"
-        )
+        line = ("SPEAKER " + rec_id + " 0 " + str(round(float(row[0]), 4)) + " "
+                + str(round(float(row[1]) - float(row[0]), 4)) + " <NA> <NA> " +
+                str(row[2]) + " <NA> <NA>")
         rttm.append(line)
 
     return rttm
 
 
-def prepare_segs_for_RTTM(
-    list_ids, out_rttm_file, audio_dir, annot_dir, split_type, skip_TNO
-):
+def prepare_segs_for_RTTM(list_ids, out_rttm_file, audio_dir, annot_dir,
+                          split_type, skip_TNO):
 
     RTTM = []  # Stores all RTTMs clubbed together for a given dataset split
 
     for main_meet_id in list_ids:
 
         # Skip TNO meetings from dev and eval sets
-        if (
-            main_meet_id.startswith("TS")
-            and split_type != "train"
-            and skip_TNO is True
-        ):
-            msg = (
-                "Skipping TNO meeting in AMI "
-                + str(split_type)
-                + " set : "
-                + str(main_meet_id)
-            )
+        if (main_meet_id.startswith("TS") and split_type != "train" and
+                skip_TNO is True):
+            msg = ("Skipping TNO meeting in AMI " + str(split_type) + " set : "
+                   + str(main_meet_id))
             logger.info(msg)
             continue
 
@@ -271,8 +250,7 @@ def prepare_segs_for_RTTM(
             list_spkr_xmls.sort()  # A, B, C, D, E etc (Speakers)
             segs = []
             spkrs_list = (
-                []
-            )  # Since non-scenario recordings contains 3-5 speakers
+                [])  # Since non-scenario recordings contains 3-5 speakers
 
             for spkr_xml_file in list_spkr_xmls:
 
@@ -286,14 +264,11 @@ def prepare_segs_for_RTTM(
                 root = tree.getroot()
 
                 # Start, end and speaker_ID from xml file
-                segs = segs + [
-                    [
-                        elem.attrib["transcriber_start"],
-                        elem.attrib["transcriber_end"],
-                        spkr_ID,
-                    ]
-                    for elem in root.iter("segment")
-                ]
+                segs = segs + [[
+                    elem.attrib["transcriber_start"],
+                    elem.attrib["transcriber_end"],
+                    spkr_ID,
+                ] for elem in root.iter("segment")]
 
             # Sort rows as per the start time (per recording)
             segs.sort(key=lambda x: float(x[0]))
@@ -404,9 +379,8 @@ def get_subsegments(merged_segs, max_subseg_dur=3.0, overlap=1.5):
     return subsegments
 
 
-def prepare_metadata(
-    rttm_file, save_dir, data_dir, filename, max_subseg_dur, overlap, mic_type
-):
+def prepare_metadata(rttm_file, save_dir, data_dir, filename, max_subseg_dur,
+                     overlap, mic_type):
     # Read RTTM, get unique meeting_IDs (from RTTM headers)
     # For each MeetingID. select that meetID -> merge -> subsegment -> json -> append
 
@@ -425,15 +399,13 @@ def prepare_metadata(
     MERGED_SEGMENTS = []
     SUBSEGMENTS = []
     for rec_id in rec_ids:
-        segs_iter = filter(
-            lambda x: x.startswith("SPEAKER " + str(rec_id)), RTTM
-        )
+        segs_iter = filter(lambda x: x.startswith("SPEAKER " + str(rec_id)),
+                           RTTM)
         gt_rttm_segs = [row.split(" ") for row in segs_iter]
 
         # Merge, subsegment and then convert to json format.
         merged_segs = merge_rttm_intervals(
-            gt_rttm_segs
-        )  # We lose speaker_ID after merging
+            gt_rttm_segs)  # We lose speaker_ID after merging
         MERGED_SEGMENTS = MERGED_SEGMENTS + merged_segs
 
         # Divide segments into smaller sub-segments
@@ -467,16 +439,8 @@ def prepare_metadata(
 
         # If multi-mic audio is selected
         if mic_type == "Array1":
-            wav_file_base_path = (
-                data_dir
-                + "/"
-                + rec_id
-                + "/audio/"
-                + rec_id
-                + "."
-                + mic_type
-                + "-"
-            )
+            wav_file_base_path = (data_dir + "/" + rec_id + "/audio/" + rec_id +
+                                  "." + mic_type + "-")
 
             f = []  # adding all 8 mics
             for i in range(8):
@@ -494,16 +458,8 @@ def prepare_metadata(
             }
         else:
             # Single mic audio
-            wav_file_path = (
-                data_dir
-                + "/"
-                + rec_id
-                + "/audio/"
-                + rec_id
-                + "."
-                + mic_type
-                + ".wav"
-            )
+            wav_file_path = (data_dir + "/" + rec_id + "/audio/" + rec_id + "."
+                             + mic_type + ".wav")
 
             # Note: key "file" without 's' is used for single-mic
             json_dict[subsegment_ID] = {
@@ -554,6 +510,7 @@ def skip(save_folder, conf, meta_files, opt_file):
 
     return skip
 
+
 if __name__ == '__main__':
 
     parser = argparse.ArgumentParser(
@@ -561,42 +518,56 @@ if __name__ == '__main__':
             --manual_annot_folder /home/data/ami/ami_public_manual_1.6.2 \
             --save_folder ./results/ --ref_rttm_dir ./results/ref_rttms \
             --meta_data_dir ./results/metadata',
-        description='AMI Data preparation') 
+        description='AMI Data preparation')
     parser.add_argument(
-        '--data_folder', required=True, help='Path to the folder where the original amicorpus is stored')
+        '--data_folder',
+        required=True,
+        help='Path to the folder where the original amicorpus is stored')
     parser.add_argument(
-        '--manual_annot_folder', required=True, help='Directory where the manual annotations are stored')
+        '--manual_annot_folder',
+        required=True,
+        help='Directory where the manual annotations are stored')
     parser.add_argument(
         '--save_folder', required=True, help='The save directory in results')
     parser.add_argument(
-        '--ref_rttm_dir', required=True, help='Directory to store reference RTTM files')
+        '--ref_rttm_dir',
+        required=True,
+        help='Directory to store reference RTTM files')
     parser.add_argument(
-        '--meta_data_dir', required=True, help='Directory to store the meta data (json) files')
+        '--meta_data_dir',
+        required=True,
+        help='Directory to store the meta data (json) files')
     parser.add_argument(
-        '--split_type', 
-        default="full_corpus_asr", 
+        '--split_type',
+        default="full_corpus_asr",
         help='Standard dataset split. See ami_splits.py for more information')
     parser.add_argument(
-        '--skip_TNO', default=True, type=strtobool, help='Skips TNO meeting recordings if True')
+        '--skip_TNO',
+        default=True,
+        type=strtobool,
+        help='Skips TNO meeting recordings if True')
     parser.add_argument(
-        '--mic_type', default="Mix-Headset", help='Type of microphone to be used')
+        '--mic_type',
+        default="Mix-Headset",
+        help='Type of microphone to be used')
     parser.add_argument(
-        '--vad_type', default="oracle", help='Type of VAD. Kept for future when VAD will be added')
+        '--vad_type',
+        default="oracle",
+        help='Type of VAD. Kept for future when VAD will be added')
     parser.add_argument(
-        '--max_subseg_dur', 
-        default=3.0, 
-        type=float, 
-        help='Duration in seconds of a subsegments to be prepared from larger segments')
+        '--max_subseg_dur',
+        default=3.0,
+        type=float,
+        help='Duration in seconds of a subsegments to be prepared from larger segments'
+    )
     parser.add_argument(
-        '--overlap', default=1.5, type=float, help='Overlap duration in seconds between adjacent subsegments')
+        '--overlap',
+        default=1.5,
+        type=float,
+        help='Overlap duration in seconds between adjacent subsegments')
 
     args = parser.parse_args()
     print(args)
 
-    prepare_ami(
-        args.data_folder, 
-        args.manual_annot_folder, 
-        args.save_folder, 
-        args.ref_rttm_dir, 
-        args.meta_data_dir
-        )
\ No newline at end of file
+    prepare_ami(args.data_folder, args.manual_annot_folder, args.save_folder,
+                args.ref_rttm_dir, args.meta_data_dir)
diff --git a/dataset/ami/ami_splits.py b/dataset/ami/ami_splits.py
index 52a8ddc04..010638a39 100644
--- a/dataset/ami/ami_splits.py
+++ b/dataset/ami/ami_splits.py
@@ -1,3 +1,16 @@
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 """
 AMI corpus contained 100 hours of meeting recording.
 This script returns the standard train, dev and eval split for AMI corpus.
@@ -29,8 +42,7 @@ def get_AMI_split(split_option):
     if split_option not in ALLOWED_OPTIONS:
         print(
             f'Invalid split "{split_option}" requested!\nValid split_options are: ',
-            ALLOWED_OPTIONS,
-        )
+            ALLOWED_OPTIONS, )
         return
 
     if split_option == "scenario_only":
diff --git a/utils/dataio.py b/dataset/ami/dataio.py
similarity index 71%
rename from utils/dataio.py
rename to dataset/ami/dataio.py
index 48f792052..f7fe88157 100644
--- a/utils/dataio.py
+++ b/dataset/ami/dataio.py
@@ -1,3 +1,16 @@
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 """
 Data reading and writing.
 
@@ -5,10 +18,10 @@ Authors
  * qingenz123@126.com (Qingen ZHAO) 2022
  
 """
-
 import os
 import pickle
 
+
 def save_pkl(obj, file):
     """Save an object in pkl format.
 
@@ -31,6 +44,7 @@ def save_pkl(obj, file):
     with open(file, "wb") as f:
         pickle.dump(obj, f)
 
+
 def load_pickle(pickle_path):
     """Utility function for loading .pkl pickle files.
 
@@ -48,6 +62,7 @@ def load_pickle(pickle_path):
         out = pickle.load(f)
     return out
 
+
 def load_pkl(file):
     """Loads a pkl file.
 
@@ -79,4 +94,4 @@ def load_pkl(file):
             return pickle.load(f)
     finally:
         if os.path.isfile(file + ".lock"):
-            os.remove(file + ".lock")
\ No newline at end of file
+            os.remove(file + ".lock")
diff --git a/utils/DER.py b/paddlespeech/vector/utils/DER.py
similarity index 80%
rename from utils/DER.py
rename to paddlespeech/vector/utils/DER.py
index 11dfa8cfa..5b62094df 100755
--- a/utils/DER.py
+++ b/paddlespeech/vector/utils/DER.py
@@ -1,3 +1,16 @@
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 """Calculates Diarization Error Rate (DER) which is the sum of Missed Speaker (MS),
 False Alarm (FA), and Speaker Error Rate (SER) using md-eval-22.pl from NIST RT Evaluation.
 
@@ -26,7 +39,6 @@ ERROR_SPEAKER_TIME = re.compile(r"(?<=SPEAKER ERROR TIME =)[\d.]+")
 def rectify(arr):
     """Corrects corner cases and converts scores into percentage.
     """
-
     # Numerator and denominator both 0.
     arr[np.isnan(arr)] = 0
 
@@ -38,12 +50,11 @@ def rectify(arr):
 
 
 def DER(
-    ref_rttm,
-    sys_rttm,
-    ignore_overlap=False,
-    collar=0.25,
-    individual_file_scores=False,
-):
+        ref_rttm,
+        sys_rttm,
+        ignore_overlap=False,
+        collar=0.25,
+        individual_file_scores=False, ):
     """Computes Missed Speaker percentage (MS), False Alarm (FA),
     Speaker Error Rate (SER), and Diarization Error Rate (DER).
 
@@ -118,25 +129,20 @@ def DER(
         ]
 
         scored_speaker_times = np.array(
-            [float(m) for m in SCORED_SPEAKER_TIME.findall(stdout)]
-        )
+            [float(m) for m in SCORED_SPEAKER_TIME.findall(stdout)])
 
         miss_speaker_times = np.array(
-            [float(m) for m in MISS_SPEAKER_TIME.findall(stdout)]
-        )
+            [float(m) for m in MISS_SPEAKER_TIME.findall(stdout)])
 
         fa_speaker_times = np.array(
-            [float(m) for m in FA_SPEAKER_TIME.findall(stdout)]
-        )
+            [float(m) for m in FA_SPEAKER_TIME.findall(stdout)])
 
         error_speaker_times = np.array(
-            [float(m) for m in ERROR_SPEAKER_TIME.findall(stdout)]
-        )
+            [float(m) for m in ERROR_SPEAKER_TIME.findall(stdout)])
 
         with np.errstate(invalid="ignore", divide="ignore"):
             tot_error_times = (
-                miss_speaker_times + fa_speaker_times + error_speaker_times
-            )
+                miss_speaker_times + fa_speaker_times + error_speaker_times)
             miss_speaker_frac = miss_speaker_times / scored_speaker_times
             fa_speaker_frac = fa_speaker_times / scored_speaker_times
             sers_frac = error_speaker_times / scored_speaker_times
@@ -153,13 +159,19 @@ def DER(
         else:
             return miss_speaker[-1], fa_speaker[-1], sers[-1], ders[-1]
 
+
 if __name__ == '__main__':
 
-    parser = argparse.ArgumentParser(description='Compute Diarization Error Rate')
+    parser = argparse.ArgumentParser(
+        description='Compute Diarization Error Rate')
     parser.add_argument(
-        '--ref_rttm', required=True, help='the path of reference/groundtruth RTTM file')
+        '--ref_rttm',
+        required=True,
+        help='the path of reference/groundtruth RTTM file')
     parser.add_argument(
-        '--sys_rttm', required=True, help='the path of the system generated RTTM file')
+        '--sys_rttm',
+        required=True,
+        help='the path of the system generated RTTM file')
     parser.add_argument(
         '--individual_file',
         default=False,
@@ -176,4 +188,5 @@ if __name__ == '__main__':
     print(args)
 
     der = DER(args.ref_rttm, args.sys_rttm)
-    print("miss_speaker: %.3f%% fa_speaker: %.3f%% sers: %.3f%% ders: %.3f%%" % (der[0], der[1], der[2], der[-1]))
\ No newline at end of file
+    print("miss_speaker: %.3f%% fa_speaker: %.3f%% sers: %.3f%% ders: %.3f%%" %
+          (der[0], der[1], der[2], der[-1]))
diff --git a/utils/md-eval.pl b/paddlespeech/vector/utils/md-eval.pl
similarity index 100%
rename from utils/md-eval.pl
rename to paddlespeech/vector/utils/md-eval.pl

From 2775235c8d24ccf4e8b24e834c8c0c7b687c4d92 Mon Sep 17 00:00:00 2001
From: qingen <qingenz123@126.com>
Date: Tue, 18 Jan 2022 09:58:54 +0800
Subject: [PATCH 6/9] [vector] add AMI data preparation scripts

---
 dataset/ami/ami_prepare.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/dataset/ami/ami_prepare.py b/dataset/ami/ami_prepare.py
index 44993cead..c2f884780 100644
--- a/dataset/ami/ami_prepare.py
+++ b/dataset/ami/ami_prepare.py
@@ -32,7 +32,7 @@ import json
 from ami_splits import get_AMI_split
 from distutils.util import strtobool
 
-from utils.dataio import (
+from dataio import (
     load_pkl,
     save_pkl, )
 

From 9d32f62f48826331f53ad2eee54d9a38ca00d105 Mon Sep 17 00:00:00 2001
From: qingen <qingenz123@126.com>
Date: Thu, 20 Jan 2022 16:59:58 +0800
Subject: [PATCH 7/9] [vector] add AMI data preparation scripts

---
 dataset/ami/README.md                         |  5 --
 examples/ami/README.md                        | 13 +++++
 .../ami/diarization}/.gitignore               |  0
 .../ami/diarization/local}/ami_prepare.py     |  1 -
 .../ami/diarization/local}/ami_splits.py      |  0
 examples/ami/diarization/local/data.sh        | 47 +++++++++++++++++++
 .../ami/diarization/local}/dataio.py          |  0
 examples/ami/diarization/path.sh              | 15 ++++++
 examples/ami/diarization/run.sh               | 14 ++++++
 examples/ami/diarization/utils                |  1 +
 {paddlespeech/vector/utils => utils}/DER.py   |  0
 .../vector/utils => utils}/md-eval.pl         |  0
 12 files changed, 90 insertions(+), 6 deletions(-)
 delete mode 100644 dataset/ami/README.md
 create mode 100644 examples/ami/README.md
 rename {dataset/ami => examples/ami/diarization}/.gitignore (100%)
 rename {dataset/ami => examples/ami/diarization/local}/ami_prepare.py (99%)
 rename {dataset/ami => examples/ami/diarization/local}/ami_splits.py (100%)
 create mode 100755 examples/ami/diarization/local/data.sh
 rename {dataset/ami => examples/ami/diarization/local}/dataio.py (100%)
 create mode 100644 examples/ami/diarization/path.sh
 create mode 100644 examples/ami/diarization/run.sh
 create mode 120000 examples/ami/diarization/utils
 rename {paddlespeech/vector/utils => utils}/DER.py (100%)
 rename {paddlespeech/vector/utils => utils}/md-eval.pl (100%)

diff --git a/dataset/ami/README.md b/dataset/ami/README.md
deleted file mode 100644
index ac65eedf6..000000000
--- a/dataset/ami/README.md
+++ /dev/null
@@ -1,5 +0,0 @@
-# [AMI](https://groups.inf.ed.ac.uk/ami/corpus/)
-
-The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings. For a gentle introduction to the corpus, see the [corpus overview](https://groups.inf.ed.ac.uk/ami/corpus/overview.shtml). To access the data, follow the directions given [there](https://groups.inf.ed.ac.uk/ami/download). Around two-thirds of the data has been elicited using a scenario in which the participants play different roles in a design team, taking a design project from kick-off to completion over the course of a day. The rest consists of naturally occurring meetings in a range of domains. 
-
-Detailed information can be found in the [documentation section](http://groups.inf.ed.ac.uk/ami/corpus/datasets.shtml).
diff --git a/examples/ami/README.md b/examples/ami/README.md
new file mode 100644
index 000000000..8d2ed5183
--- /dev/null
+++ b/examples/ami/README.md
@@ -0,0 +1,13 @@
+# Speaker Diarization on AMI corpus
+
+## About the AMI corpus:
+"The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals synchronized to a common timeline. These include close-talking and far-field microphones, individual and room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings, the participants also have unsynchronized pens available to them that record what is written. The meetings were recorded in English using three different rooms with different acoustic properties, and include mostly non-native speakers." See [ami overview](http://groups.inf.ed.ac.uk/ami/corpus/overview.shtml) for more details.
+
+## About the example
+The script performs diarization using x-vectors(TDNN,ECAPA-TDNN) on the AMI mix-headset data. We demonstrate the use of different clustering methods: AHC, spectral.
+
+## How to Run
+Use the following command to run diarization on AMI corpus.
+`bash ./run.sh` 
+
+## Results (DER) coming soon! :)
\ No newline at end of file
diff --git a/dataset/ami/.gitignore b/examples/ami/diarization/.gitignore
similarity index 100%
rename from dataset/ami/.gitignore
rename to examples/ami/diarization/.gitignore
diff --git a/dataset/ami/ami_prepare.py b/examples/ami/diarization/local/ami_prepare.py
similarity index 99%
rename from dataset/ami/ami_prepare.py
rename to examples/ami/diarization/local/ami_prepare.py
index c2f884780..b7bb8e67e 100644
--- a/dataset/ami/ami_prepare.py
+++ b/examples/ami/diarization/local/ami_prepare.py
@@ -567,7 +567,6 @@ if __name__ == '__main__':
         help='Overlap duration in seconds between adjacent subsegments')
 
     args = parser.parse_args()
-    print(args)
 
     prepare_ami(args.data_folder, args.manual_annot_folder, args.save_folder,
                 args.ref_rttm_dir, args.meta_data_dir)
diff --git a/dataset/ami/ami_splits.py b/examples/ami/diarization/local/ami_splits.py
similarity index 100%
rename from dataset/ami/ami_splits.py
rename to examples/ami/diarization/local/ami_splits.py
diff --git a/examples/ami/diarization/local/data.sh b/examples/ami/diarization/local/data.sh
new file mode 100755
index 000000000..da2c546d4
--- /dev/null
+++ b/examples/ami/diarization/local/data.sh
@@ -0,0 +1,47 @@
+#!/bin/bash
+
+stage=1
+
+data_folder=/home/data/ami/amicorpus #e.g., /path/to/amicorpus/
+manual_annot_folder=/home/data/ami/ami_public_manual_1.6.2 #e.g., /path/to/ami_public_manual_1.6.2/
+
+save_folder=results
+ref_rttm_dir=results/ref_rttms
+meta_data_dir=results/metadata
+
+set=L
+
+. ${MAIN_ROOT}/utils/parse_options.sh || exit 1;
+set -u
+set -o pipefail
+
+mkdir -p ${save_folder}
+
+if [ ${stage} -le 0 ]; then
+    # Download AMI corpus, You need around 10GB of free space to get whole data
+    # The signals are too large to package in this way,
+    # so you need to use the chooser to indicate which ones you wish to download
+    echo "Please follow https://groups.inf.ed.ac.uk/ami/download/ to download the data."
+    echo "Annotations: AMI manual annotations v1.6.2 "
+    echo "Signals: Scenario Meetings/Non Scenario Meetings, some sessions recommended but not all"
+    echo "media streams: Headset mix, recommended first"
+    exit 0;
+fi
+
+if [ ${stage} -le 1 ]; then
+    echo "AMI Data preparation"
+
+    python local/ami_prepare.py  --data_folder ${data_folder} \
+            --manual_annot_folder ${manual_annot_folder} \
+            --save_folder ${save_folder} --ref_rttm_dir ${ref_rttm_dir} \
+            --meta_data_dir ${meta_data_dir} 
+    
+    if [ $? -ne 0 ]; then
+        echo "Prepare AMI failed. Please check log message."
+        exit 1
+    fi
+            
+fi
+
+echo "AMI data preparation done."
+exit 0
diff --git a/dataset/ami/dataio.py b/examples/ami/diarization/local/dataio.py
similarity index 100%
rename from dataset/ami/dataio.py
rename to examples/ami/diarization/local/dataio.py
diff --git a/examples/ami/diarization/path.sh b/examples/ami/diarization/path.sh
new file mode 100644
index 000000000..601461131
--- /dev/null
+++ b/examples/ami/diarization/path.sh
@@ -0,0 +1,15 @@
+export MAIN_ROOT=`realpath ${PWD}/../../../`
+
+export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH}
+export LC_ALL=C
+
+export PYTHONDONTWRITEBYTECODE=1
+# Use UTF-8 in Python to avoid UnicodeDecodeError when LC_ALL=C
+export PYTHONIOENCODING=UTF-8
+export PYTHONPATH=${MAIN_ROOT}:${PYTHONPATH}
+
+export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/lib/
+
+# model exp
+#MODEL=ECAPA_TDNN
+#export BIN_DIR=${MAIN_ROOT}/paddlespeech/vector/exps/${MODEL}/bin
diff --git a/examples/ami/diarization/run.sh b/examples/ami/diarization/run.sh
new file mode 100644
index 000000000..91d4b706a
--- /dev/null
+++ b/examples/ami/diarization/run.sh
@@ -0,0 +1,14 @@
+#!/bin/bash
+
+. path.sh || exit 1;
+set -e
+
+stage=1
+
+
+. ${MAIN_ROOT}/utils/parse_options.sh || exit 1;
+
+if [ ${stage} -le 1 ]; then
+    # prepare data
+    bash ./local/data.sh || exit -1
+fi
\ No newline at end of file
diff --git a/examples/ami/diarization/utils b/examples/ami/diarization/utils
new file mode 120000
index 000000000..973afe674
--- /dev/null
+++ b/examples/ami/diarization/utils
@@ -0,0 +1 @@
+../../../utils
\ No newline at end of file
diff --git a/paddlespeech/vector/utils/DER.py b/utils/DER.py
similarity index 100%
rename from paddlespeech/vector/utils/DER.py
rename to utils/DER.py
diff --git a/paddlespeech/vector/utils/md-eval.pl b/utils/md-eval.pl
similarity index 100%
rename from paddlespeech/vector/utils/md-eval.pl
rename to utils/md-eval.pl

From 1899200caee11eff44e71bd4804b75d0059f2f67 Mon Sep 17 00:00:00 2001
From: qingen <qingenz123@126.com>
Date: Mon, 24 Jan 2022 15:14:20 +0800
Subject: [PATCH 8/9] [vector] add AMI data preparation scripts

---
 examples/ami/README.md                           | 12 +-----------
 examples/ami/{diarization => sd0}/.gitignore     |  0
 examples/ami/sd0/README.md                       | 13 +++++++++++++
 .../{diarization => sd0}/local/ami_prepare.py    |  0
 .../ami/{diarization => sd0}/local/ami_splits.py |  0
 examples/ami/{diarization => sd0}/local/data.sh  | 16 +++++++++-------
 .../ami/{diarization => sd0}/local/dataio.py     |  0
 examples/ami/{diarization => sd0}/path.sh        |  0
 examples/ami/{diarization => sd0}/run.sh         |  0
 examples/ami/{diarization => sd0}/utils          |  0
 10 files changed, 23 insertions(+), 18 deletions(-)
 rename examples/ami/{diarization => sd0}/.gitignore (100%)
 create mode 100644 examples/ami/sd0/README.md
 rename examples/ami/{diarization => sd0}/local/ami_prepare.py (100%)
 rename examples/ami/{diarization => sd0}/local/ami_splits.py (100%)
 rename examples/ami/{diarization => sd0}/local/data.sh (67%)
 rename examples/ami/{diarization => sd0}/local/dataio.py (100%)
 rename examples/ami/{diarization => sd0}/path.sh (100%)
 rename examples/ami/{diarization => sd0}/run.sh (100%)
 rename examples/ami/{diarization => sd0}/utils (100%)

diff --git a/examples/ami/README.md b/examples/ami/README.md
index 8d2ed5183..a038eaebe 100644
--- a/examples/ami/README.md
+++ b/examples/ami/README.md
@@ -1,13 +1,3 @@
 # Speaker Diarization on AMI corpus
 
-## About the AMI corpus:
-"The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals synchronized to a common timeline. These include close-talking and far-field microphones, individual and room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings, the participants also have unsynchronized pens available to them that record what is written. The meetings were recorded in English using three different rooms with different acoustic properties, and include mostly non-native speakers." See [ami overview](http://groups.inf.ed.ac.uk/ami/corpus/overview.shtml) for more details.
-
-## About the example
-The script performs diarization using x-vectors(TDNN,ECAPA-TDNN) on the AMI mix-headset data. We demonstrate the use of different clustering methods: AHC, spectral.
-
-## How to Run
-Use the following command to run diarization on AMI corpus.
-`bash ./run.sh` 
-
-## Results (DER) coming soon! :)
\ No newline at end of file
+* sd0 - speaker diarization by AHC,SC base on x-vectors
diff --git a/examples/ami/diarization/.gitignore b/examples/ami/sd0/.gitignore
similarity index 100%
rename from examples/ami/diarization/.gitignore
rename to examples/ami/sd0/.gitignore
diff --git a/examples/ami/sd0/README.md b/examples/ami/sd0/README.md
new file mode 100644
index 000000000..ffe95741a
--- /dev/null
+++ b/examples/ami/sd0/README.md
@@ -0,0 +1,13 @@
+# Speaker Diarization on AMI corpus
+
+## About the AMI corpus:
+"The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals synchronized to a common timeline. These include close-talking and far-field microphones, individual and room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings, the participants also have unsynchronized pens available to them that record what is written. The meetings were recorded in English using three different rooms with different acoustic properties, and include mostly non-native speakers." See [ami overview](http://groups.inf.ed.ac.uk/ami/corpus/overview.shtml) for more details.
+
+## About the example
+The script performs diarization using x-vectors(TDNN,ECAPA-TDNN) on the AMI mix-headset data. We demonstrate the use of different clustering methods: AHC, spectral.
+
+## How to Run
+Use the following command to run diarization on AMI corpus.
+`bash ./run.sh` 
+
+## Results (DER) coming soon! :)
diff --git a/examples/ami/diarization/local/ami_prepare.py b/examples/ami/sd0/local/ami_prepare.py
similarity index 100%
rename from examples/ami/diarization/local/ami_prepare.py
rename to examples/ami/sd0/local/ami_prepare.py
diff --git a/examples/ami/diarization/local/ami_splits.py b/examples/ami/sd0/local/ami_splits.py
similarity index 100%
rename from examples/ami/diarization/local/ami_splits.py
rename to examples/ami/sd0/local/ami_splits.py
diff --git a/examples/ami/diarization/local/data.sh b/examples/ami/sd0/local/data.sh
similarity index 67%
rename from examples/ami/diarization/local/data.sh
rename to examples/ami/sd0/local/data.sh
index da2c546d4..70f929531 100755
--- a/examples/ami/diarization/local/data.sh
+++ b/examples/ami/sd0/local/data.sh
@@ -2,12 +2,13 @@
 
 stage=1
 
-data_folder=/home/data/ami/amicorpus #e.g., /path/to/amicorpus/
-manual_annot_folder=/home/data/ami/ami_public_manual_1.6.2 #e.g., /path/to/ami_public_manual_1.6.2/
+TARGET_DIR=${MAIN_ROOT}/dataset/ami
+data_folder=${TARGET_DIR}/amicorpus #e.g., /path/to/amicorpus/
+manual_annot_folder=${TARGET_DIR}/ami_public_manual_1.6.2 #e.g., /path/to/ami_public_manual_1.6.2/
 
-save_folder=results
-ref_rttm_dir=results/ref_rttms
-meta_data_dir=results/metadata
+save_folder=${MAIN_ROOT}/dataset/ami/results
+ref_rttm_dir=${save_folder}/ref_rttms
+meta_data_dir=${save_folder}/metadata
 
 set=L
 
@@ -23,8 +24,9 @@ if [ ${stage} -le 0 ]; then
     # so you need to use the chooser to indicate which ones you wish to download
     echo "Please follow https://groups.inf.ed.ac.uk/ami/download/ to download the data."
     echo "Annotations: AMI manual annotations v1.6.2 "
-    echo "Signals: Scenario Meetings/Non Scenario Meetings, some sessions recommended but not all"
-    echo "media streams: Headset mix, recommended first"
+    echo "Signals: "
+    echo "1) Select one or more AMI meetings: the IDs please follow ./ami_split.py"
+    echo "2) Select media streams: Just select Headset mix"
     exit 0;
 fi
 
diff --git a/examples/ami/diarization/local/dataio.py b/examples/ami/sd0/local/dataio.py
similarity index 100%
rename from examples/ami/diarization/local/dataio.py
rename to examples/ami/sd0/local/dataio.py
diff --git a/examples/ami/diarization/path.sh b/examples/ami/sd0/path.sh
similarity index 100%
rename from examples/ami/diarization/path.sh
rename to examples/ami/sd0/path.sh
diff --git a/examples/ami/diarization/run.sh b/examples/ami/sd0/run.sh
similarity index 100%
rename from examples/ami/diarization/run.sh
rename to examples/ami/sd0/run.sh
diff --git a/examples/ami/diarization/utils b/examples/ami/sd0/utils
similarity index 100%
rename from examples/ami/diarization/utils
rename to examples/ami/sd0/utils

From 9c2a23e15eedd3142319964c2571daa1e259d3de Mon Sep 17 00:00:00 2001
From: qingen <qingenz123@126.com>
Date: Mon, 24 Jan 2022 18:57:10 +0800
Subject: [PATCH 9/9] [vector] add AMI data preparation scripts

---
 examples/ami/sd0/local/data.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/ami/sd0/local/data.sh b/examples/ami/sd0/local/data.sh
index 70f929531..478ec432d 100755
--- a/examples/ami/sd0/local/data.sh
+++ b/examples/ami/sd0/local/data.sh
@@ -6,7 +6,7 @@ TARGET_DIR=${MAIN_ROOT}/dataset/ami
 data_folder=${TARGET_DIR}/amicorpus #e.g., /path/to/amicorpus/
 manual_annot_folder=${TARGET_DIR}/ami_public_manual_1.6.2 #e.g., /path/to/ami_public_manual_1.6.2/
 
-save_folder=${MAIN_ROOT}/dataset/ami/results
+save_folder=${MAIN_ROOT}/examples/ami/sd0/data
 ref_rttm_dir=${save_folder}/ref_rttms
 meta_data_dir=${save_folder}/metadata