polinaeterna HF staff commited on
Commit
8db4a65
1 Parent(s): f3bf4e9

get local paths to audio files

Browse files
Files changed (1) hide show
  1. multilingual_librispeech.py +63 -27
multilingual_librispeech.py CHANGED
@@ -45,7 +45,10 @@ English, German, Dutch, Spanish, French, Italian, Portuguese, Polish.
45
  """
46
 
47
  _URL = "http://www.openslr.org/94"
48
- _DL_URL_FORMAT = "data/mls_{name}"
 
 
 
49
 
50
 
51
  class MultilingualLibrispeechConfig(datasets.BuilderConfig):
@@ -97,20 +100,28 @@ class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
97
  )
98
 
99
  def _split_generators(self, dl_manager):
100
-
 
 
 
101
  download_transcript = partial(
102
- download_extract_transcript, dl_manager=dl_manager, root_dir=self.config.data_root_dir
103
  )
104
- download_audio = partial(
105
- download_audio_archives, dl_manager=dl_manager, root_dir=self.config.data_root_dir
 
 
 
106
  )
107
  download_limited_ids = partial(
108
- download_extract_limited_ids, dl_manager=dl_manager, root_dir=self.config.data_root_dir
109
  )
110
 
111
  train_kwargs = {
112
  "transcript_path": download_transcript(split="train"),
113
- "audio_archives": download_audio(split="train")
 
 
114
  }
115
 
116
  train_splits = [
@@ -137,18 +148,22 @@ class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
137
  datasets.SplitGenerator(
138
  name=datasets.Split.VALIDATION, gen_kwargs={
139
  "transcript_path": download_transcript(split="dev"),
140
- "audio_archives": download_audio(split="dev"),
 
 
141
  }
142
  ),
143
  datasets.SplitGenerator(
144
  name=datasets.Split.TEST, gen_kwargs={
145
  "transcript_path": download_transcript(split="test"),
146
- "audio_archives": download_audio(split="test"),
 
 
147
  }
148
  ),
149
  ]
150
 
151
- def _generate_examples(self, transcript_path, audio_archives, limited_ids_paths=None):
152
  """Generate examples from a Multilingual LibriSpeech data dir."""
153
  transcripts = dict()
154
  with open(transcript_path, "r", encoding="utf-8") as file:
@@ -164,7 +179,7 @@ class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
164
 
165
  limited_ids = set(limited_ids)
166
 
167
- for audio_archive in audio_archives:
168
  # TODO: check that archive doesn't contain needed ids
169
  # if limited_ids and audio_archive not in limited_ids_archives_names:
170
  # continue
@@ -179,9 +194,11 @@ class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
179
  # this only can be true in limited supervision sets ("train.9h" and "train.1h")
180
  continue
181
 
 
 
182
  yield audio_filename, {
183
- "file": audio_filename,
184
- "audio": {"path": audio_filename, "bytes": file.read()},
185
  "text": audio_transcript,
186
  "speaker_id": speaker_id,
187
  "chapter_id": chapter_id,
@@ -190,7 +207,7 @@ class MultilingualLibrispeech(datasets.GeneratorBasedBuilder):
190
 
191
 
192
  def download_extract_limited_ids(dl_manager, root_dir, sub_folder):
193
- """Download and extract all handles.txt files containing ids for limited supervision train sets. """
194
 
195
  sub_path = os.path.join(root_dir, "train", sub_folder)
196
 
@@ -201,33 +218,52 @@ def download_extract_limited_ids(dl_manager, root_dir, sub_folder):
201
  # "limited_supervision/1h/0/handles.txt", "limited_supervision/1h/1/handles.txt", ...
202
  limited_ids_paths = [os.path.join(sub_path, str(i), "handles.txt") for i in range(6)]
203
 
204
- limited_ids_paths = dl_manager.download_and_extract(limited_ids_paths)
205
 
206
  return limited_ids_paths
207
 
208
 
209
  def download_extract_transcript(dl_manager, root_dir, split):
210
- """Downloading and extracting file with audio transcriptions. """
211
- transcript_path = os.path.join(root_dir, split, "transcripts.txt")
212
- return dl_manager.download_and_extract(transcript_path)
213
-
214
-
215
- def download_audio_archives(dl_manager, root_dir, split):
216
- """Prepare archives with audio files for iterating over them.
217
 
218
  Return:
219
- audio_archives (List `Generator`): list of generators to iterate over files in each audio archive.
220
  """
 
 
 
221
 
 
222
  # each split contains many .tar.gz archives with its audio files
223
  # audio_filenames.txt contains the names of these archives
224
  split_dir = os.path.join(root_dir, split)
225
  audio_filenames_path = dl_manager.download(os.path.join(split_dir, "audio_filenames.txt"))
226
 
227
- with xopen(audio_filenames_path, "r", encoding="utf-8") as file:
228
  audio_filenames = [line.strip() for line in file.readlines()]
229
 
230
- archive_paths = dl_manager.download([os.path.join(split_dir, "audio", filename) for filename in audio_filenames])
231
- audio_archives = [dl_manager.iter_archive(archive_path) for archive_path in archive_paths]
232
 
233
- return audio_archives
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
45
  """
46
 
47
  _URL = "http://www.openslr.org/94"
48
+
49
+ _BASE_URL = "https://huggingface.co/datasets/facebook/multilingual_librispeech/resolve/main/"
50
+
51
+ _DL_URL_FORMAT = _BASE_URL + "data/mls_{name}"
52
 
53
 
54
  class MultilingualLibrispeechConfig(datasets.BuilderConfig):
 
100
  )
101
 
102
  def _split_generators(self, dl_manager):
103
+ download_kwargs = {
104
+ "dl_manager": dl_manager,
105
+ "root_dir": self.config.data_root_dir
106
+ }
107
  download_transcript = partial(
108
+ download_extract_transcript, **download_kwargs
109
  )
110
+ download_audio_non_streaming = partial(
111
+ download_extract_audio_archives, **download_kwargs
112
+ )
113
+ download_audio_streaming = partial(
114
+ download_audio_archives, **download_kwargs
115
  )
116
  download_limited_ids = partial(
117
+ download_extract_limited_ids, **download_kwargs
118
  )
119
 
120
  train_kwargs = {
121
  "transcript_path": download_transcript(split="train"),
122
+ "audio_archives": download_audio_streaming(split="train"),
123
+ "local_audio_archives_paths": download_audio_non_streaming(split="train")
124
+ if not dl_manager.is_streaming else None
125
  }
126
 
127
  train_splits = [
 
148
  datasets.SplitGenerator(
149
  name=datasets.Split.VALIDATION, gen_kwargs={
150
  "transcript_path": download_transcript(split="dev"),
151
+ "audio_archives": download_audio_streaming(split="dev"),
152
+ "local_audio_archives_paths": download_audio_non_streaming(split="dev")
153
+ if not dl_manager.is_streaming else None
154
  }
155
  ),
156
  datasets.SplitGenerator(
157
  name=datasets.Split.TEST, gen_kwargs={
158
  "transcript_path": download_transcript(split="test"),
159
+ "audio_archives": download_audio_streaming(split="test"),
160
+ "local_audio_archives_paths": download_audio_non_streaming(split="test")
161
+ if not dl_manager.is_streaming else None
162
  }
163
  ),
164
  ]
165
 
166
+ def _generate_examples(self, transcript_path, audio_archives, local_audio_archives_paths, limited_ids_paths=None):
167
  """Generate examples from a Multilingual LibriSpeech data dir."""
168
  transcripts = dict()
169
  with open(transcript_path, "r", encoding="utf-8") as file:
 
179
 
180
  limited_ids = set(limited_ids)
181
 
182
+ for archive_idx, audio_archive in enumerate(audio_archives):
183
  # TODO: check that archive doesn't contain needed ids
184
  # if limited_ids and audio_archive not in limited_ids_archives_names:
185
  # continue
 
194
  # this only can be true in limited supervision sets ("train.9h" and "train.1h")
195
  continue
196
 
197
+ path = os.path.join(local_audio_archives_paths[archive_idx], audio_filename)\
198
+ if local_audio_archives_paths else audio_filename
199
  yield audio_filename, {
200
+ "file": path if local_audio_archives_paths else None,
201
+ "audio": {"path": path, "bytes": file.read()},
202
  "text": audio_transcript,
203
  "speaker_id": speaker_id,
204
  "chapter_id": chapter_id,
 
207
 
208
 
209
  def download_extract_limited_ids(dl_manager, root_dir, sub_folder):
210
+ """Download handles.txt files containing ids for limited supervision train sets. """
211
 
212
  sub_path = os.path.join(root_dir, "train", sub_folder)
213
 
 
218
  # "limited_supervision/1h/0/handles.txt", "limited_supervision/1h/1/handles.txt", ...
219
  limited_ids_paths = [os.path.join(sub_path, str(i), "handles.txt") for i in range(6)]
220
 
221
+ limited_ids_paths = dl_manager.download(limited_ids_paths)
222
 
223
  return limited_ids_paths
224
 
225
 
226
  def download_extract_transcript(dl_manager, root_dir, split):
227
+ """
228
+ Download file with audio transcriptions.
 
 
 
 
 
229
 
230
  Return:
231
+ path (str): path to locally extracted `transcripts.txt` file
232
  """
233
+ transcript_path = os.path.join(root_dir, split, "transcripts.txt")
234
+ return dl_manager.download(transcript_path)
235
+
236
 
237
+ def download_audio_archive_paths(dl_manager, root_dir, split):
238
  # each split contains many .tar.gz archives with its audio files
239
  # audio_filenames.txt contains the names of these archives
240
  split_dir = os.path.join(root_dir, split)
241
  audio_filenames_path = dl_manager.download(os.path.join(split_dir, "audio_filenames.txt"))
242
 
243
+ with open(audio_filenames_path, "r", encoding="utf-8") as file:
244
  audio_filenames = [line.strip() for line in file.readlines()]
245
 
246
+ return dl_manager.download([os.path.join(split_dir, "audio", filename) for filename in audio_filenames])
 
247
 
248
+
249
+ # for non-streaming case
250
+ def download_extract_audio_archives(dl_manager, root_dir, split):
251
+ """
252
+ Download and extract audio archives locally.
253
+
254
+ Return:
255
+ archive_paths (List `str`): paths to locally extracted archives
256
+ """
257
+ archive_paths = download_audio_archive_paths(dl_manager, root_dir, split)
258
+ return [dl_manager.extract(archive_path) for archive_path in archive_paths]
259
+
260
+
261
+ # for streaming case
262
+ def download_audio_archives(dl_manager, root_dir, split):
263
+ """Prepare archives with audio files for iterating over them.
264
+
265
+ Return:
266
+ audio_archives (List `Generator`): list of generators to iterate over files in each audio archive.
267
+ """
268
+ archive_paths = download_audio_archive_paths(dl_manager, root_dir, split)
269
+ return [dl_manager.iter_archive(archive_path) for archive_path in archive_paths]