[s2t] mv dataset into paddlespeech.dataset (#3183)

* mv dataset into paddlespeech.dataset

* add aidatatang

* fix import
pull/3193/head
Hui Zhang 1 year ago committed by GitHub
parent 3ad55a31e7
commit 35d874c532
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@ -18,139 +18,7 @@ Manifest file is a json-format file with each line containing the
meta data (i.e. audio filepath, transcript and audio duration)
of each audio file in the data set.
"""
import argparse
import codecs
import json
import os
from pathlib import Path
import soundfile
from utils.utility import download
from utils.utility import unpack
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')
URL_ROOT = 'http://www.openslr.org/resources/62'
# URL_ROOT = 'https://openslr.magicdatatech.com/resources/62'
DATA_URL = URL_ROOT + '/aidatatang_200zh.tgz'
MD5_DATA = '6e0f4f39cd5f667a7ee53c397c8d0949'
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
"--target_dir",
default=DATA_HOME + "/aidatatang_200zh",
type=str,
help="Directory to save the dataset. (default: %(default)s)")
parser.add_argument(
"--manifest_prefix",
default="manifest",
type=str,
help="Filepath prefix for output manifests. (default: %(default)s)")
args = parser.parse_args()
def create_manifest(data_dir, manifest_path_prefix):
print("Creating manifest %s ..." % manifest_path_prefix)
json_lines = []
transcript_path = os.path.join(data_dir, 'transcript',
'aidatatang_200_zh_transcript.txt')
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
data_types = ['train', 'dev', 'test']
for dtype in data_types:
del json_lines[:]
total_sec = 0.0
total_text = 0.0
total_num = 0
audio_dir = os.path.join(data_dir, 'corpus/', dtype)
for subfolder, _, filelist in sorted(os.walk(audio_dir)):
for fname in filelist:
if not fname.endswith('.wav'):
continue
audio_path = os.path.abspath(os.path.join(subfolder, fname))
audio_id = os.path.basename(fname)[:-4]
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')
manifest_dir = os.path.dirname(manifest_path_prefix)
meta_path = os.path.join(manifest_dir, dtype) + '.meta'
with open(meta_path, 'w') as f:
print(f"{dtype}:", file=f)
print(f"{total_num} utts", file=f)
print(f"{total_sec / (60*60)} h", file=f)
print(f"{total_text} text", file=f)
print(f"{total_text / total_sec} text/sec", file=f)
print(f"{total_sec / total_num} sec/utt", file=f)
def prepare_dataset(url, md5sum, target_dir, manifest_path, subset):
"""Download, unpack and create manifest file."""
data_dir = os.path.join(target_dir, subset)
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, 'corpus')
for subfolder, dirlist, filelist in sorted(os.walk(audio_dir)):
for sub in dirlist:
print(f"unpack dir {sub}...")
for folder, _, filelist in sorted(
os.walk(os.path.join(subfolder, sub))):
for ftar in filelist:
unpack(os.path.join(folder, ftar), folder, True)
else:
print("Skip downloading and unpacking. Data already exists in %s." %
target_dir)
create_manifest(data_dir, manifest_path)
def main():
if args.target_dir.startswith('~'):
args.target_dir = os.path.expanduser(args.target_dir)
prepare_dataset(
url=DATA_URL,
md5sum=MD5_DATA,
target_dir=args.target_dir,
manifest_path=args.manifest_prefix,
subset='aidatatang_200zh')
print("Data download and manifest prepare done!")
from paddlespeech.dataset.aidatatang_200zh import aidatatang_200zh_main
if __name__ == '__main__':
main()
aidatatang_200zh_main()

@ -1,3 +0,0 @@
# [Aishell1](http://openslr.elda.org/33/)
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. )

@ -18,143 +18,7 @@ Manifest file is a json-format file with each line containing the
meta data (i.e. audio filepath, transcript and audio duration)
of each audio file in the data set.
"""
import argparse
import codecs
import json
import os
from pathlib import Path
import soundfile
from utils.utility import download
from utils.utility import unpack
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')
URL_ROOT = 'http://openslr.elda.org/resources/33'
# URL_ROOT = 'https://openslr.magicdatatech.com/resources/33'
DATA_URL = URL_ROOT + '/data_aishell.tgz'
MD5_DATA = '2f494334227864a8a8fec932999db9d8'
RESOURCE_URL = URL_ROOT + '/resource_aishell.tgz'
MD5_RESOURCE = '957d480a0fcac85fc18e550756f624e5'
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
"--target_dir",
default=DATA_HOME + "/Aishell",
type=str,
help="Directory to save the dataset. (default: %(default)s)")
parser.add_argument(
"--manifest_prefix",
default="manifest",
type=str,
help="Filepath prefix for output manifests. (default: %(default)s)")
args = parser.parse_args()
def create_manifest(data_dir, manifest_path_prefix):
print("Creating manifest %s ..." % manifest_path_prefix)
json_lines = []
transcript_path = os.path.join(data_dir, 'transcript',
'aishell_transcript_v0.8.txt')
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
data_types = ['train', 'dev', 'test']
for dtype in data_types:
del json_lines[:]
total_sec = 0.0
total_text = 0.0
total_num = 0
audio_dir = os.path.join(data_dir, 'wav', dtype)
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:
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')
manifest_dir = os.path.dirname(manifest_path_prefix)
meta_path = os.path.join(manifest_dir, dtype) + '.meta'
with open(meta_path, 'w') as f:
print(f"{dtype}:", file=f)
print(f"{total_num} utts", file=f)
print(f"{total_sec / (60*60)} h", file=f)
print(f"{total_text} text", file=f)
print(f"{total_text / total_sec} text/sec", file=f)
print(f"{total_sec / total_num} sec/utt", file=f)
def prepare_dataset(url, md5sum, target_dir, manifest_path=None):
"""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." %
target_dir)
if manifest_path:
create_manifest(data_dir, manifest_path)
def main():
if args.target_dir.startswith('~'):
args.target_dir = os.path.expanduser(args.target_dir)
prepare_dataset(
url=DATA_URL,
md5sum=MD5_DATA,
target_dir=args.target_dir,
manifest_path=args.manifest_prefix)
prepare_dataset(
url=RESOURCE_URL,
md5sum=MD5_RESOURCE,
target_dir=args.target_dir,
manifest_path=None)
print("Data download and manifest prepare done!")
from paddlespeech.dataset.aishell import aishell_main
if __name__ == '__main__':
main()
aishell_main()

@ -28,8 +28,8 @@ from multiprocessing.pool import Pool
import distutils.util
import soundfile
from utils.utility import download
from utils.utility import unpack
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unpack
URL_ROOT = "http://openslr.elda.org/resources/12"
#URL_ROOT = "https://openslr.magicdatatech.com/resources/12"

@ -27,8 +27,8 @@ from multiprocessing.pool import Pool
import soundfile
from utils.utility import download
from utils.utility import unpack
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unpack
URL_ROOT = "http://openslr.elda.org/resources/31"
URL_TRAIN_CLEAN = URL_ROOT + "/train-clean-5.tar.gz"

@ -29,8 +29,8 @@ import os
import soundfile
from utils.utility import download
from utils.utility import unpack
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unpack
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')

@ -29,8 +29,8 @@ import os
import soundfile
from utils.utility import download
from utils.utility import unzip
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unzip
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')

@ -27,8 +27,8 @@ from pathlib import Path
import soundfile
from utils.utility import download
from utils.utility import unpack
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unpack
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')

@ -28,7 +28,7 @@ from pathlib import Path
import soundfile
from utils.utility import unzip
from paddlespeech.dataset.download import unzip
URL_ROOT = ""
MD5_DATA = "45c68037c7fdfe063a43c851f181fb2d"

@ -31,9 +31,9 @@ from pathlib import Path
import soundfile
from utils.utility import check_md5sum
from utils.utility import download
from utils.utility import unzip
from paddlespeech.dataset.download import check_md5sum
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unzip
# all the data will be download in the current data/voxceleb directory default
DATA_HOME = os.path.expanduser('.')

@ -27,9 +27,9 @@ from pathlib import Path
import soundfile
from utils.utility import check_md5sum
from utils.utility import download
from utils.utility import unzip
from paddlespeech.dataset.download import check_md5sum
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unzip
# all the data will be download in the current data/voxceleb directory default
DATA_HOME = os.path.expanduser('.')

@ -28,9 +28,9 @@ import subprocess
import soundfile
from utils.utility import download_multi
from utils.utility import getfile_insensitive
from utils.utility import unpack
from paddlespeech.dataset.download import download_multi
from paddlespeech.dataset.download import getfile_insensitive
from paddlespeech.dataset.download import unpack
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')

@ -14,8 +14,8 @@
from audio_search import app
from fastapi.testclient import TestClient
from utils.utility import download
from utils.utility import unpack
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unpack
client = TestClient(app)

@ -14,8 +14,8 @@
from fastapi.testclient import TestClient
from vpr_search import app
from utils.utility import download
from utils.utility import unpack
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unpack
client = TestClient(app)

@ -13,3 +13,7 @@
# limitations under the License.
import _locale
_locale._getdefaultlocale = (lambda *args: ['en_US', 'utf8'])
__version__ = '0.0.0'
__commit__ = '9cf8c1985a98bb380c183116123672976bdfe5c9'

@ -0,0 +1,14 @@
# 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.
from .aidatatang_200zh import main as aidatatang_200zh_main

@ -0,0 +1,157 @@
# Copyright (c) 2021 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.
"""Prepare aidatatang_200zh mandarin dataset
Download, unpack and create manifest files.
Manifest file is a json-format file with each line containing the
meta data (i.e. audio filepath, transcript and audio duration)
of each audio file in the data set.
"""
import argparse
import codecs
import json
import os
from pathlib import Path
import soundfile
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unpack
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')
URL_ROOT = 'http://www.openslr.org/resources/62'
# URL_ROOT = 'https://openslr.magicdatatech.com/resources/62'
DATA_URL = URL_ROOT + '/aidatatang_200zh.tgz'
MD5_DATA = '6e0f4f39cd5f667a7ee53c397c8d0949'
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
"--target_dir",
default=DATA_HOME + "/aidatatang_200zh",
type=str,
help="Directory to save the dataset. (default: %(default)s)")
parser.add_argument(
"--manifest_prefix",
default="manifest",
type=str,
help="Filepath prefix for output manifests. (default: %(default)s)")
args = parser.parse_args()
def create_manifest(data_dir, manifest_path_prefix):
print("Creating manifest %s ..." % manifest_path_prefix)
json_lines = []
transcript_path = os.path.join(data_dir, 'transcript',
'aidatatang_200_zh_transcript.txt')
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
data_types = ['train', 'dev', 'test']
for dtype in data_types:
del json_lines[:]
total_sec = 0.0
total_text = 0.0
total_num = 0
audio_dir = os.path.join(data_dir, 'corpus/', dtype)
for subfolder, _, filelist in sorted(os.walk(audio_dir)):
for fname in filelist:
if not fname.endswith('.wav'):
continue
audio_path = os.path.abspath(os.path.join(subfolder, fname))
audio_id = os.path.basename(fname)[:-4]
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')
manifest_dir = os.path.dirname(manifest_path_prefix)
meta_path = os.path.join(manifest_dir, dtype) + '.meta'
with open(meta_path, 'w') as f:
print(f"{dtype}:", file=f)
print(f"{total_num} utts", file=f)
print(f"{total_sec / (60*60)} h", file=f)
print(f"{total_text} text", file=f)
print(f"{total_text / total_sec} text/sec", file=f)
print(f"{total_sec / total_num} sec/utt", file=f)
def prepare_dataset(url, md5sum, target_dir, manifest_path, subset):
"""Download, unpack and create manifest file."""
data_dir = os.path.join(target_dir, subset)
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, 'corpus')
for subfolder, dirlist, filelist in sorted(os.walk(audio_dir)):
for sub in dirlist:
print(f"unpack dir {sub}...")
for folder, _, filelist in sorted(
os.walk(os.path.join(subfolder, sub))):
for ftar in filelist:
unpack(os.path.join(folder, ftar), folder, True)
else:
print("Skip downloading and unpacking. Data already exists in %s." %
target_dir)
create_manifest(data_dir, manifest_path)
def main():
print(f"args: {args}")
if args.target_dir.startswith('~'):
args.target_dir = os.path.expanduser(args.target_dir)
prepare_dataset(
url=DATA_URL,
md5sum=MD5_DATA,
target_dir=args.target_dir,
manifest_path=args.manifest_prefix,
subset='aidatatang_200zh')
print("Data download and manifest prepare done!")
if __name__ == '__main__':
main()

@ -0,0 +1,58 @@
# [Aishell1](http://openslr.elda.org/33/)
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. )
## Dataset Architecture
```bash
data_aishell
├── transcript # text 目录
└── wav # wav 目录
├── dev # dev 目录
│ ├── S0724 # spk 目录
│ ├── S0725
│ ├── S0726
├── train
│ ├── S0724
│ ├── S0725
│ ├── S0726
├── test
│ ├── S0724
│ ├── S0725
│ ├── S0726
data_aishell
├── transcript
│ └── aishell_transcript_v0.8.txt # 文本标注文件
└── wav
├── dev
│ ├── S0724
│ │ ├── BAC009S0724W0121.wav # S0724 的音频
│ │ ├── BAC009S0724W0122.wav
│ │ ├── BAC009S0724W0123.wav
├── test
│ ├── S0724
│ │ ├── BAC009S0724W0121.wav
│ │ ├── BAC009S0724W0122.wav
│ │ ├── BAC009S0724W0123.wav
├── train
│ ├── S0724
│ │ ├── BAC009S0724W0121.wav
│ │ ├── BAC009S0724W0122.wav
│ │ ├── BAC009S0724W0123.wav
标注文件格式: <utt> <tokens>
> head data_aishell/transcript/aishell_transcript_v0.8.txt
BAC009S0002W0122 而 对 楼市 成交 抑制 作用 最 大 的 限 购
BAC009S0002W0123 也 成为 地方 政府 的 眼中 钉
BAC009S0002W0124 自 六月 底 呼和浩特 市 率先 宣布 取消 限 购 后
BAC009S0002W0125 各地 政府 便 纷纷 跟进
BAC009S0002W0126 仅 一 个 多 月 的 时间 里
BAC009S0002W0127 除了 北京 上海 广州 深圳 四 个 一 线 城市 和 三亚 之外
BAC009S0002W0128 四十六 个 限 购 城市 当中
BAC009S0002W0129 四十一 个 已 正式 取消 或 变相 放松 了 限 购
BAC009S0002W0130 财政 金融 政策 紧随 其后 而来
BAC009S0002W0131 显示 出 了 极 强 的 威力
```

@ -0,0 +1,18 @@
# 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.
from .aishell import check_dataset
from .aishell import create_manifest
from .aishell import download_dataset
from .aishell import main as aishell_main
from .aishell import prepare_dataset

@ -0,0 +1,229 @@
# Copyright (c) 2021 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.
"""Prepare Aishell mandarin dataset
Download, unpack and create manifest files.
Manifest file is a json-format file with each line containing the
meta data (i.e. audio filepath, transcript and audio duration)
of each audio file in the data set.
"""
import argparse
import codecs
import json
import os
from pathlib import Path
import soundfile
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unpack
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')
URL_ROOT = 'http://openslr.elda.org/resources/33'
# URL_ROOT = 'https://openslr.magicdatatech.com/resources/33'
DATA_URL = URL_ROOT + '/data_aishell.tgz'
MD5_DATA = '2f494334227864a8a8fec932999db9d8'
RESOURCE_URL = URL_ROOT + '/resource_aishell.tgz'
MD5_RESOURCE = '957d480a0fcac85fc18e550756f624e5'
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
"--target_dir",
default=DATA_HOME + "/Aishell",
type=str,
help="Directory to save the dataset. (default: %(default)s)")
parser.add_argument(
"--manifest_prefix",
default="manifest",
type=str,
help="Filepath prefix for output manifests. (default: %(default)s)")
args = parser.parse_args()
def create_manifest(data_dir, manifest_path_prefix):
print("Creating manifest %s ..." % os.path.join(data_dir,
manifest_path_prefix))
json_lines = []
transcript_path = os.path.join(data_dir, 'transcript',
'aishell_transcript_v0.8.txt')
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
data_metas = dict()
data_types = ['train', 'dev', 'test']
for dtype in data_types:
del json_lines[:]
total_sec = 0.0
total_text = 0.0
total_num = 0
audio_dir = os.path.join(data_dir, 'wav', dtype)
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:
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()

@ -19,91 +19,16 @@ import zipfile
from typing import Text
__all__ = [
"check_md5sum", "getfile_insensitive", "download_multi", "download",
"unpack", "unzip", "md5file", "print_arguments", "add_arguments",
"get_commandline_args"
"check_md5sum",
"getfile_insensitive",
"download_multi",
"download",
"unpack",
"unzip",
"md5file",
]
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)
def md5file(fname):
hash_md5 = hashlib.md5()
f = open(fname, "rb")

@ -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)

@ -26,8 +26,8 @@ from pathlib import Path
import soundfile
from utils.utility import download
from utils.utility import unpack
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unpack
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')

@ -25,8 +25,8 @@ from pathlib import Path
import soundfile
from utils.utility import download
from utils.utility import unpack
from paddlespeech.dataset.download import download
from paddlespeech.dataset.download import unpack
DATA_HOME = os.path.expanduser('~/.cache/paddle/dataset/speech')

@ -6,8 +6,8 @@ from pathlib import Path
import jsonlines
from utils.utility import add_arguments
from utils.utility import print_arguments
from paddlespeech.utils.argparse import add_arguments
from paddlespeech.utils.argparse import print_arguments
def main(args):

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