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