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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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"""Prepare THCHS-30 mandarin dataset
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Download, unpack and create manifest files.
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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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of each audio file in the data set.
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"""
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import argparse
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import codecs
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import json
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import os
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from multiprocessing.pool import Pool
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from pathlib import Path
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import soundfile
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from utils.utility import download
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from utils.utility import unpack
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DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')
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URL_ROOT = 'http://www.openslr.org/resources/18'
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# URL_ROOT = 'https://openslr.magicdatatech.com/resources/18'
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DATA_URL = URL_ROOT + '/data_thchs30.tgz'
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TEST_NOISE_URL = URL_ROOT + '/test-noise.tgz'
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RESOURCE_URL = URL_ROOT + '/resource.tgz'
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MD5_DATA = '2d2252bde5c8429929e1841d4cb95e90'
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MD5_TEST_NOISE = '7e8a985fb965b84141b68c68556c2030'
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MD5_RESOURCE = 'c0b2a565b4970a0c4fe89fefbf2d97e1'
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument(
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"--target_dir",
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default=DATA_HOME + "/THCHS30",
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type=str,
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help="Directory to save the dataset. (default: %(default)s)")
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parser.add_argument(
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"--manifest_prefix",
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default="manifest",
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type=str,
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help="Filepath prefix for output manifests. (default: %(default)s)")
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args = parser.parse_args()
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def read_trn(filepath):
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"""read trn file.
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word text in first line.
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syllable text in second line.
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phoneme text in third line.
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Args:
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filepath (str): trn path.
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Returns:
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list(str): (word, syllable, phone)
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"""
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texts = []
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with open(filepath, 'r') as f:
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lines = f.read().strip().split('\n')
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assert len(lines) == 3, lines
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# charactor text, remove withespace
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texts.append(''.join(lines[0].split()))
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texts.extend(lines[1:])
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return texts
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def resolve_symlink(filepath):
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"""resolve symlink which content is norm file.
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Args:
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filepath (str): norm file symlink.
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"""
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sym_path = Path(filepath)
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relative_link = sym_path.read_text().strip()
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relative = Path(relative_link)
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relpath = sym_path.parent / relative
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return relpath.resolve()
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def create_manifest(data_dir, manifest_path_prefix):
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print("Creating manifest %s ..." % manifest_path_prefix)
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json_lines = []
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data_types = ['train', 'dev', 'test']
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for dtype in data_types:
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del json_lines[:]
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total_sec = 0.0
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total_text = 0.0
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total_num = 0
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audio_dir = os.path.join(data_dir, dtype)
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for subfolder, _, filelist in sorted(os.walk(audio_dir)):
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for fname in filelist:
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file_path = os.path.join(subfolder, fname)
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if file_path.endswith('.wav'):
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audio_path = os.path.abspath(file_path)
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text_path = resolve_symlink(audio_path + '.trn')
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else:
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continue
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assert os.path.exists(audio_path) and os.path.exists(text_path)
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audio_id = os.path.basename(audio_path)[:-4]
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word_text, syllable_text, phone_text = read_trn(text_path)
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audio_data, samplerate = soundfile.read(audio_path)
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duration = float(len(audio_data) / samplerate)
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# not dump alignment infos
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json_lines.append(
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json.dumps(
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{
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'utt': audio_id,
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'feat': audio_path,
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'feat_shape': (duration, ), # second
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'text': word_text, # charactor
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'syllable': syllable_text,
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'phone': phone_text,
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},
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ensure_ascii=False))
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total_sec += duration
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total_text += len(word_text)
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total_num += 1
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manifest_path = manifest_path_prefix + '.' + dtype
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with codecs.open(manifest_path, 'w', 'utf-8') as fout:
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for line in json_lines:
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fout.write(line + '\n')
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with open(dtype + '.meta', 'w') as f:
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print(f"{dtype}:", file=f)
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print(f"{total_num} utts", file=f)
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print(f"{total_sec / (60*60)} h", file=f)
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print(f"{total_text} text", file=f)
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print(f"{total_text / total_sec} text/sec", file=f)
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print(f"{total_sec / total_num} sec/utt", file=f)
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def prepare_dataset(url, md5sum, target_dir, manifest_path, subset):
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"""Download, unpack and create manifest file."""
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datadir = os.path.join(target_dir, subset)
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if not os.path.exists(datadir):
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filepath = download(url, md5sum, target_dir)
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unpack(filepath, target_dir)
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else:
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print("Skip downloading and unpacking. Data already exists in %s." %
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target_dir)
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if subset == 'data_thchs30':
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create_manifest(datadir, manifest_path)
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def main():
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if args.target_dir.startswith('~'):
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args.target_dir = os.path.expanduser(args.target_dir)
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tasks = [
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(DATA_URL, MD5_DATA, args.target_dir, args.manifest_prefix,
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"data_thchs30"),
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(TEST_NOISE_URL, MD5_TEST_NOISE, args.target_dir, args.manifest_prefix,
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"test-noise"),
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(RESOURCE_URL, MD5_RESOURCE, args.target_dir, args.manifest_prefix,
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"resource"),
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]
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with Pool(7) as pool:
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pool.starmap(prepare_dataset, tasks)
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print("Data download and manifest prepare done!")
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if __name__ == '__main__':
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main()
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