TianYuan
3 years ago
parent
1c9c122b3b
commit
7d4eff2b86
@ -0,0 +1,2 @@
|
||||
this is the example of MFA for thchs30 dataset
|
||||
cd a0 run run.sh to get start
|
||||
@ -0,0 +1,26 @@
|
||||
#! /usr/bin/env bash
|
||||
|
||||
stage=-1
|
||||
stop_stage=100
|
||||
|
||||
source ${MAIN_ROOT}/utils/parse_options.sh
|
||||
|
||||
mkdir -p data
|
||||
TARGET_DIR=${MAIN_ROOT}/examples/dataset
|
||||
mkdir -p ${TARGET_DIR}
|
||||
|
||||
if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then
|
||||
# download data, generate manifests
|
||||
python3 ${TARGET_DIR}/thchs30/thchs30.py \
|
||||
--manifest_prefix="data/manifest" \
|
||||
--target_dir="${TARGET_DIR}/thchs30"
|
||||
|
||||
if [ $? -ne 0 ]; then
|
||||
echo "Prepare THCHS-30 failed. Terminated."
|
||||
exit 1
|
||||
fi
|
||||
|
||||
fi
|
||||
|
||||
echo "THCHS-30 data preparation done."
|
||||
exit 0
|
||||
@ -0,0 +1,112 @@
|
||||
# Copyright (c) 2021 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.
|
||||
"""Recorganize THCHS-30 for MFA
|
||||
read manifest.train from root-dir
|
||||
Link *.wav to output-dir
|
||||
dump *.lab from manifest.train, such as: text、syllable and phone
|
||||
Manifest file is a json-format file with each line containing the
|
||||
meta data (i.e. audio filepath, transcript and audio duration)
|
||||
"""
|
||||
import argparse
|
||||
import os
|
||||
from pathlib import Path
|
||||
from typing import Union
|
||||
|
||||
from deepspeech.frontend.utility import read_manifest
|
||||
|
||||
|
||||
def link_wav(root_dir: Union[str, Path], output_dir: Union[str, Path]):
|
||||
manifest_path = root_dir / "manifest.train"
|
||||
manifest_jsons = read_manifest(manifest_path)
|
||||
for line_json in manifest_jsons:
|
||||
wav_path = line_json['feat']
|
||||
wav_name = wav_path.split("/")[-1]
|
||||
new_wav_path = output_dir / wav_name
|
||||
os.symlink(wav_path, new_wav_path)
|
||||
|
||||
|
||||
def link_lexicon(root_dir: Union[str, Path],
|
||||
output_dir: Union[str, Path],
|
||||
script_type='phone'):
|
||||
manifest_path = root_dir / "manifest.train"
|
||||
manifest_jsons = read_manifest(manifest_path)
|
||||
line_json = manifest_jsons[0]
|
||||
wav_path = line_json['feat']
|
||||
|
||||
if script_type == 'phone':
|
||||
# find lexicon.txt in THCHS-30
|
||||
grader_father = os.path.abspath(
|
||||
os.path.dirname(wav_path) + os.path.sep + "..")
|
||||
grader_father = Path(grader_father).expanduser()
|
||||
lexicon_name = "lexicon.txt"
|
||||
lexicon_father_dir = "lm_phone"
|
||||
lexicon_path = grader_father / lexicon_father_dir / lexicon_name
|
||||
elif script_type == 'syllable':
|
||||
# find thchs30_pinyin2phone in dir of this py file
|
||||
py_dir_path = os.path.split(os.path.realpath(__file__))[0]
|
||||
py_dir_path = Path(py_dir_path).expanduser()
|
||||
lexicon_path = py_dir_path / "thchs30_pinyin2phone"
|
||||
else:
|
||||
# script_type == 'text'
|
||||
# find thchs30_cn2phone in dir of this py file
|
||||
py_dir_path = os.path.split(os.path.realpath(__file__))[0]
|
||||
py_dir_path = Path(py_dir_path).expanduser()
|
||||
lexicon_path = py_dir_path / "thchs30_cn2phone"
|
||||
|
||||
new_lexicon_name = script_type + ".lexicon"
|
||||
new_lexicon_path = os.path.dirname(output_dir) + "/" + new_lexicon_name
|
||||
os.symlink(lexicon_path, new_lexicon_path)
|
||||
|
||||
|
||||
def dump_lab(root_dir: Union[str, Path],
|
||||
output_dir: Union[str, Path],
|
||||
script_type='phone'):
|
||||
# script_type can in {'text', 'syllable', 'phone'}
|
||||
manifest_path = root_dir / "manifest.train"
|
||||
manifest_jsons = read_manifest(manifest_path)
|
||||
for line_json in manifest_jsons:
|
||||
utt_id = line_json['utt']
|
||||
transcript_name = utt_id + ".lab"
|
||||
transcript_path = output_dir / transcript_name
|
||||
with open(transcript_path, 'wt') as wf:
|
||||
wf.write(line_json[script_type] + "\n")
|
||||
|
||||
|
||||
def reorganize_thchs30(root_dir: Union[str, Path],
|
||||
output_dir: Union[str, Path]=None,
|
||||
script_type='phone'):
|
||||
root_dir = Path(root_dir).expanduser()
|
||||
output_dir = Path(output_dir).expanduser()
|
||||
output_dir.mkdir(parents=True, exist_ok=True)
|
||||
link_wav(root_dir, output_dir)
|
||||
dump_lab(root_dir, output_dir, script_type)
|
||||
link_lexicon(root_dir, output_dir, script_type)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Reorganize THCHS-30 dataset for MFA")
|
||||
parser.add_argument("--root-dir", type=str, help="path to thchs30 dataset.")
|
||||
parser.add_argument(
|
||||
"--output-dir",
|
||||
type=str,
|
||||
help="path to save outputs(audio and transcriptions)")
|
||||
|
||||
parser.add_argument(
|
||||
"--script-type",
|
||||
type=str,
|
||||
default="phone",
|
||||
help="type of lab (text'/'syllable'/'phone')")
|
||||
args = parser.parse_args()
|
||||
reorganize_thchs30(args.root_dir, args.output_dir, args.script_type)
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,14 @@
|
||||
export MAIN_ROOT=${PWD}/../../../
|
||||
|
||||
export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH}
|
||||
export LC_ALL=C
|
||||
|
||||
# Use UTF-8 in Python to avoid UnicodeDecodeError when LC_ALL=C
|
||||
export PYTHONIOENCODING=UTF-8
|
||||
export PYTHONPATH=${MAIN_ROOT}:${PYTHONPATH}
|
||||
|
||||
export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/lib/
|
||||
|
||||
|
||||
MODEL=deepspeech2
|
||||
export BIN_DIR=${MAIN_ROOT}/deepspeech/exps/${MODEL}/bin
|
||||
@ -0,0 +1,40 @@
|
||||
#!/bin/bash
|
||||
set -e
|
||||
source path.sh
|
||||
stage=0
|
||||
stop_stage=100
|
||||
EXP_DIR=exp
|
||||
# LEXICON_NAME in {'phone', 'syllable', 'text'}
|
||||
LEXICON_NAME='phone'
|
||||
# get machine's cpu core number
|
||||
NUM_JOBS=`grep 'processor' /proc/cpuinfo | sort -u | wc -l`
|
||||
NUM_JOBS=$((NUM_JOBS/2))
|
||||
source ${MAIN_ROOT}/utils/parse_options.sh || exit 1;
|
||||
|
||||
# download dataset、unzip and generate manifest
|
||||
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
|
||||
# prepare data
|
||||
bash ./local/data.sh || exit -1
|
||||
fi
|
||||
|
||||
# reorganize dataset for MFA
|
||||
if [ ! -d $EXP_DIR/thchs30_corpus ]; then
|
||||
echo "reorganizing thchs30 corpus..."
|
||||
python local/recorganize_thchs30.py --root-dir=./data --output-dir=$EXP_DIR/thchs30_corpus --script-type=$LEXICON_NAME
|
||||
echo "reorganization done."
|
||||
fi
|
||||
# MFA is in tools
|
||||
export PATH="${MAIN_ROOT}/tools/montreal-forced-aligner/bin"
|
||||
|
||||
if [ ! -d "$EXP_DIR/thchs30_alignment" ]; then
|
||||
echo "Start MFA training..."
|
||||
mfa_train_and_align $EXP_DIR/thchs30_corpus "$EXP_DIR/$LEXICON_NAME.lexicon" $EXP_DIR/thchs30_alignment -o $EXP_DIR/thchs30_model --clean --verbose --temp_directory exp/.mfa_train_and_align --num_jobs $NUM_JOBS
|
||||
echo "training done! \nresults: $EXP_DIR/thchs30_alignment \nmodel: $EXP_DIR/thchs30_model\n"
|
||||
fi
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in new issue