Hui Zhang
4 years ago
committed by
GitHub
commit
43b52082c3
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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import Dict
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from typing import List
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from typing import Text
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import textgrid
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def segment_alignment(alignment: List[int], blank_id=0) -> List[List[int]]:
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"""segment ctc alignment ids by continuous blank and repeat label.
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Args:
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alignment (List[int]): ctc alignment id sequence.
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e.g. [0, 0, 0, 1, 1, 1, 2, 0, 0, 3]
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blank_id (int, optional): blank id. Defaults to 0.
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Returns:
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List[List[int]]: token align, segment aligment id sequence.
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e.g. [[0, 0, 0, 1, 1, 1], [2], [0, 0, 3]]
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"""
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# convert alignment to a praat format, which is a doing phonetics
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# by computer and helps analyzing alignment
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align_segs = []
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# get frames level duration for each token
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start = 0
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end = 0
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while end < len(alignment):
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while end < len(alignment) and alignment[end] == blank_id: # blank
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end += 1
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if end == len(alignment):
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align_segs[-1].extend(alignment[start:])
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break
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end += 1
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while end < len(alignment) and alignment[end - 1] == alignment[
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end]: # repeat label
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end += 1
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align_segs.append(alignment[start:end])
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start = end
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return align_segs
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def align_to_tierformat(align_segs: List[List[int]],
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subsample: int,
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token_dict: Dict[int, Text],
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blank_id=0) -> List[Text]:
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"""Generate textgrid.Interval format from alignment segmentations.
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Args:
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align_segs (List[List[int]]): segmented ctc alignment ids.
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subsample (int): 25ms frame_length, 10ms hop_length, 1/subsample
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token_dict (Dict[int, Text]): int -> str map.
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Returns:
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List[Text]: list of textgrid.Interval text, str(start, end, text).
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"""
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hop_length = 10 # ms
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second_ms = 1000 # ms
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frame_per_second = second_ms / hop_length # 25ms frame_length, 10ms hop_length
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second_per_frame = 1.0 / frame_per_second
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begin = 0
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duration = 0
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tierformat = []
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for idx, tokens in enumerate(align_segs):
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token_len = len(tokens)
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token = tokens[-1]
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# time duration in second
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duration = token_len * subsample * second_per_frame
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if idx < len(align_segs) - 1:
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print(f"{begin:.2f} {begin + duration:.2f} {token_dict[token]}")
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tierformat.append(
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f"{begin:.2f} {begin + duration:.2f} {token_dict[token]}\n")
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else:
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for i in tokens:
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if i != blank_id:
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token = i
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break
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print(f"{begin:.2f} {begin + duration:.2f} {token_dict[token]}")
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tierformat.append(
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f"{begin:.2f} {begin + duration:.2f} {token_dict[token]}\n")
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begin = begin + duration
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return tierformat
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def generate_textgrid(maxtime: float,
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intervals: List[Text],
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output: Text,
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name: Text='ali') -> None:
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"""Create alignment textgrid file.
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Args:
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maxtime (float): audio duartion.
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intervals (List[Text]): ctc output alignment. e.g. "start-time end-time word" per item.
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output (Text): textgrid filepath.
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name (Text, optional): tier or layer name. Defaults to 'ali'.
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"""
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# Download Praat: https://www.fon.hum.uva.nl/praat/
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avg_interval = maxtime / (len(intervals) + 1)
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print(f"average second/token: {avg_interval}")
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margin = 0.0001
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tg = textgrid.TextGrid(maxTime=maxtime)
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tier = textgrid.IntervalTier(name=name, maxTime=maxtime)
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i = 0
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for dur in intervals:
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s, e, text = dur.split()
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tier.add(minTime=float(s) + margin, maxTime=float(e), mark=text)
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tg.append(tier)
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tg.write(output)
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print("successfully generator textgrid {}.".format(output))
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@ -0,0 +1,43 @@
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#! /usr/bin/env bash
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if [ $# != 2 ];then
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echo "usage: ${0} config_path ckpt_path_prefix"
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exit -1
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fi
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ngpu=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
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echo "using $ngpu gpus..."
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device=gpu
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if [ ngpu == 0 ];then
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device=cpu
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fi
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config_path=$1
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ckpt_prefix=$2
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ckpt_name=$(basename ${ckpt_prefxi})
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mkdir -p exp
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batch_size=1
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output_dir=${ckpt_prefix}
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mkdir -p ${output_dir}
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# align dump in `result_file`
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# .tier, .TextGrid dump in `dir of result_file`
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python3 -u ${BIN_DIR}/alignment.py \
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--device ${device} \
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--nproc 1 \
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--config ${config_path} \
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--result_file ${output_dir}/${type}.align \
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--checkpoint_path ${ckpt_prefix} \
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--opts decoding.batch_size ${batch_size}
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if [ $? -ne 0 ]; then
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echo "Failed in ctc alignment!"
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exit 1
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fi
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exit 0
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#! /usr/bin/env bash
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if [ $# != 2 ];then
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echo "usage: ${0} config_path ckpt_path_prefix"
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exit -1
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fi
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ngpu=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
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echo "using $ngpu gpus..."
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device=gpu
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if [ ngpu == 0 ];then
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device=cpu
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fi
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config_path=$1
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ckpt_prefix=$2
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ckpt_name=$(basename ${ckpt_prefxi})
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mkdir -p exp
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batch_size=1
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output_dir=${ckpt_prefix}
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mkdir -p ${output_dir}
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# align dump in `result_file`
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# .tier, .TextGrid dump in `dir of result_file`
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python3 -u ${BIN_DIR}/alignment.py \
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--device ${device} \
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--nproc 1 \
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--config ${config_path} \
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--result_file ${output_dir}/${type}.align \
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--checkpoint_path ${ckpt_prefix} \
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--opts decoding.batch_size ${batch_size}
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if [ $? -ne 0 ]; then
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echo "Failed in ctc alignment!"
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exit 1
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fi
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exit 0
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#! /usr/bin/env bash
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if [ $# != 2 ];then
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echo "usage: ${0} config_path ckpt_path_prefix"
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exit -1
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fi
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ngpu=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
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echo "using $ngpu gpus..."
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device=gpu
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if [ ngpu == 0 ];then
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device=cpu
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fi
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config_path=$1
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ckpt_prefix=$2
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ckpt_name=$(basename ${ckpt_prefxi})
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mkdir -p exp
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batch_size=1
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output_dir=${ckpt_prefix}
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mkdir -p ${output_dir}
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# align dump in `result_file`
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# .tier, .TextGrid dump in `dir of result_file`
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python3 -u ${BIN_DIR}/alignment.py \
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--device ${device} \
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--nproc 1 \
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--config ${config_path} \
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--result_file ${output_dir}/${type}.align \
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--checkpoint_path ${ckpt_prefix} \
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--opts decoding.batch_size ${batch_size}
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if [ $? -ne 0 ]; then
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echo "Failed in ctc alignment!"
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exit 1
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fi
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exit 0
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