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231 lines
8.0 KiB
231 lines
8.0 KiB
# 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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from paddlespeech.utils.argparse import print_arguments
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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]
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# if no transcription for audio then skipped
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if audio_id not in transcript_dict:
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continue
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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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meta = dict()
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meta["dtype"] = dtype # train, dev, test
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meta["utts"] = total_num
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meta["hours"] = total_sec / (60 * 60)
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meta["text"] = total_text
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meta["text/sec"] = total_text / total_sec
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meta["sec/utt"] = total_sec / total_num
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data_metas[dtype] = meta
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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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for key, val in meta.items():
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print(f"{key}: {val}", file=f)
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return data_metas
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def download_dataset(url, md5sum, target_dir):
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"""Download, unpack and create manifest file."""
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data_dir = os.path.join(target_dir, 'data_aishell')
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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, 'wav')
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for subfolder, _, filelist in sorted(os.walk(audio_dir)):
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for ftar in filelist:
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unpack(os.path.join(subfolder, ftar), subfolder, True)
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else:
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print("Skip downloading and unpacking. Data already exists in %s." %
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os.path.abspath(target_dir))
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return os.path.abspath(data_dir)
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def check_dataset(data_dir):
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print(f"check dataset {os.path.abspath(data_dir)} ...")
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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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if not os.path.exists(transcript_path):
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raise FileNotFoundError(f"no transcript file found in {data_dir}.")
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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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no_label = 0
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data_types = ['train', 'dev', 'test']
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for dtype in data_types:
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audio_dir = os.path.join(data_dir, 'wav', dtype)
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if not os.path.exists(audio_dir):
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raise IOError(f"{audio_dir} does not exist.")
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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]
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# if no transcription for audio then skipped
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if audio_id not in transcript_dict:
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print(f"Warning: {audio_id} not has transcript.")
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no_label += 1
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continue
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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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assert samplerate == 16000, f"{audio_path} sample rate is {samplerate} not 16k, please check."
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print(f"Warning: {dtype} has {no_label} audio does not has transcript.")
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def prepare_dataset(url, md5sum, target_dir, manifest_path=None, check=False):
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"""Download, unpack and create manifest file."""
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data_dir = download_dataset(url, md5sum, target_dir)
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if check:
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try:
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check_dataset(data_dir)
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except Exception as e:
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raise ValueError(
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f"{data_dir} dataset format not right, please check it.")
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meta = None
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if manifest_path:
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meta = create_manifest(data_dir, manifest_path)
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return data_dir, meta
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def main():
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print_arguments(args, globals())
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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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data_dir, meta = 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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check=True)
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resource_dir, _ = prepare_dataset(
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url=RESOURCE_URL,
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md5sum=MD5_RESOURCE,
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target_dir=args.target_dir,
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manifest_path=None)
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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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