[s2t] mv dataset into paddlespeech.dataset (#3183)
* mv dataset into paddlespeech.dataset * add aidatatang * fix importpull/3193/head
Hui Zhang
2 years ago
committed by
GitHub
parent
3ad55a31e7
commit
35d874c532
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# [Aishell1](http://openslr.elda.org/33/)
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This Open Source Mandarin Speech Corpus, AISHELL-ASR0009-OS1, is 178 hours long. It is a part of AISHELL-ASR0009, of which utterance contains 11 domains, including smart home, autonomous driving, and industrial production. The whole recording was put in quiet indoor environment, using 3 different devices at the same time: high fidelity microphone (44.1kHz, 16-bit,); Android-system mobile phone (16kHz, 16-bit), iOS-system mobile phone (16kHz, 16-bit). Audios in high fidelity were re-sampled to 16kHz to build AISHELL- ASR0009-OS1. 400 speakers from different accent areas in China were invited to participate in the recording. The manual transcription accuracy rate is above 95%, through professional speech annotation and strict quality inspection. The corpus is divided into training, development and testing sets. ( This database is free for academic research, not in the commerce, if without permission. )
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# Copyright (c) 2023 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 .aidatatang_200zh import main as aidatatang_200zh_main
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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 aidatatang_200zh 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 pathlib import Path
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import soundfile
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from paddlespeech.dataset.download import download
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from paddlespeech.dataset.download 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/62'
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# URL_ROOT = 'https://openslr.magicdatatech.com/resources/62'
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DATA_URL = URL_ROOT + '/aidatatang_200zh.tgz'
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MD5_DATA = '6e0f4f39cd5f667a7ee53c397c8d0949'
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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 + "/aidatatang_200zh",
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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 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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transcript_path = os.path.join(data_dir, 'transcript',
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'aidatatang_200_zh_transcript.txt')
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transcript_dict = {}
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for line in codecs.open(transcript_path, 'r', 'utf-8'):
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line = line.strip()
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if line == '':
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continue
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audio_id, text = line.split(' ', 1)
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# remove withespace, charactor text
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text = ''.join(text.split())
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transcript_dict[audio_id] = text
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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, 'corpus/', 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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if not fname.endswith('.wav'):
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continue
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audio_path = os.path.abspath(os.path.join(subfolder, fname))
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audio_id = os.path.basename(fname)[:-4]
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utt2spk = Path(audio_path).parent.name
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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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text = transcript_dict[audio_id]
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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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'utt2spk': str(utt2spk),
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'feat': audio_path,
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'feat_shape': (duration, ), # second
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'text': 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(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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manifest_dir = os.path.dirname(manifest_path_prefix)
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meta_path = os.path.join(manifest_dir, dtype) + '.meta'
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with open(meta_path, '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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data_dir = os.path.join(target_dir, subset)
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if not os.path.exists(data_dir):
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filepath = download(url, md5sum, target_dir)
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unpack(filepath, target_dir)
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# unpack all audio tar files
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audio_dir = os.path.join(data_dir, 'corpus')
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for subfolder, dirlist, filelist in sorted(os.walk(audio_dir)):
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for sub in dirlist:
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print(f"unpack dir {sub}...")
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for folder, _, filelist in sorted(
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os.walk(os.path.join(subfolder, sub))):
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for ftar in filelist:
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unpack(os.path.join(folder, ftar), folder, True)
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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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create_manifest(data_dir, manifest_path)
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def main():
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print(f"args: {args}")
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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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prepare_dataset(
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url=DATA_URL,
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md5sum=MD5_DATA,
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target_dir=args.target_dir,
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manifest_path=args.manifest_prefix,
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subset='aidatatang_200zh')
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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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# [Aishell1](http://openslr.elda.org/33/)
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This Open Source Mandarin Speech Corpus, AISHELL-ASR0009-OS1, is 178 hours long. It is a part of AISHELL-ASR0009, of which utterance contains 11 domains, including smart home, autonomous driving, and industrial production. The whole recording was put in quiet indoor environment, using 3 different devices at the same time: high fidelity microphone (44.1kHz, 16-bit,); Android-system mobile phone (16kHz, 16-bit), iOS-system mobile phone (16kHz, 16-bit). Audios in high fidelity were re-sampled to 16kHz to build AISHELL- ASR0009-OS1. 400 speakers from different accent areas in China were invited to participate in the recording. The manual transcription accuracy rate is above 95%, through professional speech annotation and strict quality inspection. The corpus is divided into training, development and testing sets. ( This database is free for academic research, not in the commerce, if without permission. )
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## Dataset Architecture
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```bash
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data_aishell
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├── transcript # text 目录
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└── wav # wav 目录
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├── dev # dev 目录
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│ ├── S0724 # spk 目录
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│ ├── S0725
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│ ├── S0726
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├── train
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│ ├── S0724
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│ ├── S0725
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│ ├── S0726
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├── test
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│ ├── S0724
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│ ├── S0725
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│ ├── S0726
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data_aishell
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├── transcript
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│ └── aishell_transcript_v0.8.txt # 文本标注文件
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└── wav
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├── dev
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│ ├── S0724
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│ │ ├── BAC009S0724W0121.wav # S0724 的音频
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│ │ ├── BAC009S0724W0122.wav
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│ │ ├── BAC009S0724W0123.wav
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├── test
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│ ├── S0724
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│ │ ├── BAC009S0724W0121.wav
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│ │ ├── BAC009S0724W0122.wav
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│ │ ├── BAC009S0724W0123.wav
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├── train
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│ ├── S0724
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│ │ ├── BAC009S0724W0121.wav
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│ │ ├── BAC009S0724W0122.wav
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│ │ ├── BAC009S0724W0123.wav
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标注文件格式： <utt> <tokens>
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> head data_aishell/transcript/aishell_transcript_v0.8.txt
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BAC009S0002W0122 而 对 楼市 成交 抑制 作用 最 大 的 限 购
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BAC009S0002W0123 也 成为 地方 政府 的 眼中 钉
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BAC009S0002W0124 自 六月 底 呼和浩特 市 率先 宣布 取消 限 购 后
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BAC009S0002W0125 各地 政府 便 纷纷 跟进
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BAC009S0002W0126 仅 一 个 多 月 的 时间 里
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BAC009S0002W0127 除了 北京 上海 广州 深圳 四 个 一 线 城市 和 三亚 之外
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BAC009S0002W0128 四十六 个 限 购 城市 当中
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BAC009S0002W0129 四十一 个 已 正式 取消 或 变相 放松 了 限 购
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BAC009S0002W0130 财政 金融 政策 紧随 其后 而来
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BAC009S0002W0131 显示 出 了 极 强 的 威力
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```
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# Copyright (c) 2023 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 .aishell import check_dataset
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from .aishell import create_manifest
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from .aishell import download_dataset
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from .aishell import main as aishell_main
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from .aishell import prepare_dataset
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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 Aishell 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 pathlib import Path
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import soundfile
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from paddlespeech.dataset.download import download
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from paddlespeech.dataset.download import unpack
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DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')
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URL_ROOT = 'http://openslr.elda.org/resources/33'
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# URL_ROOT = 'https://openslr.magicdatatech.com/resources/33'
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DATA_URL = URL_ROOT + '/data_aishell.tgz'
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MD5_DATA = '2f494334227864a8a8fec932999db9d8'
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RESOURCE_URL = URL_ROOT + '/resource_aishell.tgz'
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MD5_RESOURCE = '957d480a0fcac85fc18e550756f624e5'
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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 + "/Aishell",
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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 create_manifest(data_dir, manifest_path_prefix):
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print("Creating manifest %s ..." % os.path.join(data_dir,
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manifest_path_prefix))
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json_lines = []
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transcript_path = os.path.join(data_dir, 'transcript',
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'aishell_transcript_v0.8.txt')
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transcript_dict = {}
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for line in codecs.open(transcript_path, 'r', 'utf-8'):
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line = line.strip()
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if line == '':
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continue
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audio_id, text = line.split(' ', 1)
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# remove withespace, charactor text
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text = ''.join(text.split())
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transcript_dict[audio_id] = text
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data_metas = dict()
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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, 'wav', 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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audio_path = os.path.abspath(os.path.join(subfolder, fname))
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||||||
|
audio_id = os.path.basename(fname)[:-4]
|
||||||
|
# if no transcription for audio then skipped
|
||||||
|
if audio_id not in transcript_dict:
|
||||||
|
continue
|
||||||
|
|
||||||
|
utt2spk = Path(audio_path).parent.name
|
||||||
|
audio_data, samplerate = soundfile.read(audio_path)
|
||||||
|
duration = float(len(audio_data) / samplerate)
|
||||||
|
text = transcript_dict[audio_id]
|
||||||
|
json_lines.append(
|
||||||
|
json.dumps(
|
||||||
|
{
|
||||||
|
'utt': audio_id,
|
||||||
|
'utt2spk': str(utt2spk),
|
||||||
|
'feat': audio_path,
|
||||||
|
'feat_shape': (duration, ), # second
|
||||||
|
'text': text
|
||||||
|
},
|
||||||
|
ensure_ascii=False))
|
||||||
|
|
||||||
|
total_sec += duration
|
||||||
|
total_text += len(text)
|
||||||
|
total_num += 1
|
||||||
|
|
||||||
|
manifest_path = manifest_path_prefix + '.' + dtype
|
||||||
|
with codecs.open(manifest_path, 'w', 'utf-8') as fout:
|
||||||
|
for line in json_lines:
|
||||||
|
fout.write(line + '\n')
|
||||||
|
|
||||||
|
meta = dict()
|
||||||
|
meta["dtype"] = dtype # train, dev, test
|
||||||
|
meta["utts"] = total_num
|
||||||
|
meta["hours"] = total_sec / (60 * 60)
|
||||||
|
meta["text"] = total_text
|
||||||
|
meta["text/sec"] = total_text / total_sec
|
||||||
|
meta["sec/utt"] = total_sec / total_num
|
||||||
|
data_metas[dtype] = meta
|
||||||
|
|
||||||
|
manifest_dir = os.path.dirname(manifest_path_prefix)
|
||||||
|
meta_path = os.path.join(manifest_dir, dtype) + '.meta'
|
||||||
|
with open(meta_path, 'w') as f:
|
||||||
|
for key, val in meta.items():
|
||||||
|
print(f"{key}: {val}", file=f)
|
||||||
|
|
||||||
|
return data_metas
|
||||||
|
|
||||||
|
|
||||||
|
def download_dataset(url, md5sum, target_dir):
|
||||||
|
"""Download, unpack and create manifest file."""
|
||||||
|
data_dir = os.path.join(target_dir, 'data_aishell')
|
||||||
|
if not os.path.exists(data_dir):
|
||||||
|
filepath = download(url, md5sum, target_dir)
|
||||||
|
unpack(filepath, target_dir)
|
||||||
|
# unpack all audio tar files
|
||||||
|
audio_dir = os.path.join(data_dir, 'wav')
|
||||||
|
for subfolder, _, filelist in sorted(os.walk(audio_dir)):
|
||||||
|
for ftar in filelist:
|
||||||
|
unpack(os.path.join(subfolder, ftar), subfolder, True)
|
||||||
|
else:
|
||||||
|
print("Skip downloading and unpacking. Data already exists in %s." %
|
||||||
|
os.path.abspath(target_dir))
|
||||||
|
return os.path.abspath(data_dir)
|
||||||
|
|
||||||
|
|
||||||
|
def check_dataset(data_dir):
|
||||||
|
print(f"check dataset {os.path.abspath(data_dir)} ...")
|
||||||
|
|
||||||
|
transcript_path = os.path.join(data_dir, 'transcript',
|
||||||
|
'aishell_transcript_v0.8.txt')
|
||||||
|
if not os.path.exists(transcript_path):
|
||||||
|
raise FileNotFoundError(f"no transcript file found in {data_dir}.")
|
||||||
|
|
||||||
|
transcript_dict = {}
|
||||||
|
for line in codecs.open(transcript_path, 'r', 'utf-8'):
|
||||||
|
line = line.strip()
|
||||||
|
if line == '':
|
||||||
|
continue
|
||||||
|
audio_id, text = line.split(' ', 1)
|
||||||
|
# remove withespace, charactor text
|
||||||
|
text = ''.join(text.split())
|
||||||
|
transcript_dict[audio_id] = text
|
||||||
|
|
||||||
|
no_label = 0
|
||||||
|
data_types = ['train', 'dev', 'test']
|
||||||
|
for dtype in data_types:
|
||||||
|
audio_dir = os.path.join(data_dir, 'wav', dtype)
|
||||||
|
if not os.path.exists(audio_dir):
|
||||||
|
raise IOError(f"{audio_dir} does not exist.")
|
||||||
|
|
||||||
|
for subfolder, _, filelist in sorted(os.walk(audio_dir)):
|
||||||
|
for fname in filelist:
|
||||||
|
audio_path = os.path.abspath(os.path.join(subfolder, fname))
|
||||||
|
audio_id = os.path.basename(fname)[:-4]
|
||||||
|
# if no transcription for audio then skipped
|
||||||
|
if audio_id not in transcript_dict:
|
||||||
|
print(f"Warning: {audio_id} not has transcript.")
|
||||||
|
no_label += 1
|
||||||
|
continue
|
||||||
|
|
||||||
|
utt2spk = Path(audio_path).parent.name
|
||||||
|
audio_data, samplerate = soundfile.read(audio_path)
|
||||||
|
assert samplerate == 16000, f"{audio_path} sample rate is {samplerate} not 16k, please check."
|
||||||
|
|
||||||
|
print(f"Warning: {dtype} has {no_label} audio does not has transcript.")
|
||||||
|
|
||||||
|
|
||||||
|
def prepare_dataset(url, md5sum, target_dir, manifest_path=None, check=False):
|
||||||
|
"""Download, unpack and create manifest file."""
|
||||||
|
data_dir = download_dataset(url, md5sum, target_dir)
|
||||||
|
|
||||||
|
if check:
|
||||||
|
try:
|
||||||
|
check_dataset(data_dir)
|
||||||
|
except Exception as e:
|
||||||
|
raise ValueError(
|
||||||
|
f"{data_dir} dataset format not right, please check it.")
|
||||||
|
|
||||||
|
meta = None
|
||||||
|
if manifest_path:
|
||||||
|
meta = create_manifest(data_dir, manifest_path)
|
||||||
|
|
||||||
|
return data_dir, meta
|
||||||
|
|
||||||
|
|
||||||
|
def main():
|
||||||
|
print(f"args: {args}")
|
||||||
|
if args.target_dir.startswith('~'):
|
||||||
|
args.target_dir = os.path.expanduser(args.target_dir)
|
||||||
|
|
||||||
|
data_dir, meta = prepare_dataset(
|
||||||
|
url=DATA_URL,
|
||||||
|
md5sum=MD5_DATA,
|
||||||
|
target_dir=args.target_dir,
|
||||||
|
manifest_path=args.manifest_prefix,
|
||||||
|
check=True)
|
||||||
|
|
||||||
|
resource_dir, _ = prepare_dataset(
|
||||||
|
url=RESOURCE_URL,
|
||||||
|
md5sum=MD5_RESOURCE,
|
||||||
|
target_dir=args.target_dir,
|
||||||
|
manifest_path=None)
|
||||||
|
|
||||||
|
print("Data download and manifest prepare done!")
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
main()
|
||||||
@ -0,0 +1,98 @@
|
|||||||
|
# Copyright (c) 2023 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.
|
||||||
|
import hashlib
|
||||||
|
import os
|
||||||
|
import sys
|
||||||
|
from typing import Text
|
||||||
|
|
||||||
|
__all__ = ["print_arguments", "add_arguments", "get_commandline_args"]
|
||||||
|
|
||||||
|
|
||||||
|
def get_commandline_args():
|
||||||
|
extra_chars = [
|
||||||
|
" ",
|
||||||
|
";",
|
||||||
|
"&",
|
||||||
|
"(",
|
||||||
|
")",
|
||||||
|
"|",
|
||||||
|
"^",
|
||||||
|
"<",
|
||||||
|
">",
|
||||||
|
"?",
|
||||||
|
"*",
|
||||||
|
"[",
|
||||||
|
"]",
|
||||||
|
"$",
|
||||||
|
"`",
|
||||||
|
'"',
|
||||||
|
"\\",
|
||||||
|
"!",
|
||||||
|
"{",
|
||||||
|
"}",
|
||||||
|
]
|
||||||
|
|
||||||
|
# Escape the extra characters for shell
|
||||||
|
argv = [
|
||||||
|
arg.replace("'", "'\\''") if all(char not in arg
|
||||||
|
for char in extra_chars) else
|
||||||
|
"'" + arg.replace("'", "'\\''") + "'" for arg in sys.argv
|
||||||
|
]
|
||||||
|
|
||||||
|
return sys.executable + " " + " ".join(argv)
|
||||||
|
|
||||||
|
|
||||||
|
def print_arguments(args, info=None):
|
||||||
|
"""Print argparse's arguments.
|
||||||
|
|
||||||
|
Usage:
|
||||||
|
|
||||||
|
.. code-block:: python
|
||||||
|
|
||||||
|
parser = argparse.ArgumentParser()
|
||||||
|
parser.add_argument("name", default="Jonh", type=str, help="User name.")
|
||||||
|
args = parser.parse_args()
|
||||||
|
print_arguments(args)
|
||||||
|
|
||||||
|
:param args: Input argparse.Namespace for printing.
|
||||||
|
:type args: argparse.Namespace
|
||||||
|
"""
|
||||||
|
filename = ""
|
||||||
|
if info:
|
||||||
|
filename = info["__file__"]
|
||||||
|
filename = os.path.basename(filename)
|
||||||
|
print(f"----------- {filename} Configuration Arguments -----------")
|
||||||
|
for arg, value in sorted(vars(args).items()):
|
||||||
|
print("%s: %s" % (arg, value))
|
||||||
|
print("-----------------------------------------------------------")
|
||||||
|
|
||||||
|
|
||||||
|
def add_arguments(argname, type, default, help, argparser, **kwargs):
|
||||||
|
"""Add argparse's argument.
|
||||||
|
|
||||||
|
Usage:
|
||||||
|
|
||||||
|
.. code-block:: python
|
||||||
|
|
||||||
|
parser = argparse.ArgumentParser()
|
||||||
|
add_argument("name", str, "Jonh", "User name.", parser)
|
||||||
|
args = parser.parse_args()
|
||||||
|
"""
|
||||||
|
type = distutils.util.strtobool if type == bool else type
|
||||||
|
argparser.add_argument(
|
||||||
|
"--" + argname,
|
||||||
|
default=default,
|
||||||
|
type=type,
|
||||||
|
help=help + ' Default: %(default)s.',
|
||||||
|
**kwargs)
|
||||||
Loading…
Reference in new issue