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README.md CHANGED
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  ---
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- pretty_name: Common Voice Corpus 9.0
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- - multilingual
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- zh-HK:
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- zh-TW:
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- - 100K<n<1M
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- source_datasets:
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- - extended|common_voice
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- task_categories:
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- - speech-processing
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- task_ids:
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- - automatic-speech-recognition
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- paperswithcode_id: common-voice
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- extra_gated_prompt: "By clicking on “Access repository” below, you also agree to not attempt to determine the identity of speakers in the Common Voice dataset."
300
  ---
301
 
302
- # Dataset Card for Common Voice Corpus 9.0
303
 
304
- ## Table of Contents
305
- - [Dataset Description](#dataset-description)
306
- - [Dataset Summary](#dataset-summary)
307
- - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
308
- - [Languages](#languages)
309
- - [Dataset Structure](#dataset-structure)
310
- - [Data Instances](#data-instances)
311
- - [Data Fields](#data-fields)
312
- - [Data Splits](#data-splits)
313
- - [Dataset Creation](#dataset-creation)
314
- - [Curation Rationale](#curation-rationale)
315
- - [Source Data](#source-data)
316
- - [Annotations](#annotations)
317
- - [Personal and Sensitive Information](#personal-and-sensitive-information)
318
- - [Considerations for Using the Data](#considerations-for-using-the-data)
319
- - [Social Impact of Dataset](#social-impact-of-dataset)
320
- - [Discussion of Biases](#discussion-of-biases)
321
- - [Other Known Limitations](#other-known-limitations)
322
- - [Additional Information](#additional-information)
323
- - [Dataset Curators](#dataset-curators)
324
- - [Licensing Information](#licensing-information)
325
- - [Citation Information](#citation-information)
326
- - [Contributions](#contributions)
327
 
328
- ## Dataset Description
329
-
330
- - **Homepage:** https://commonvoice.mozilla.org/en/datasets
331
- - **Repository:** https://github.com/common-voice/common-voice
332
- - **Paper:** https://arxiv.org/abs/1912.06670
333
- - **Leaderboard:** https://paperswithcode.com/dataset/common-voice
334
- - **Point of Contact:** [Anton Lozhkov](mailto:anton@huggingface.co)
335
-
336
- ### Dataset Summary
337
-
338
- The Common Voice dataset consists of a unique MP3 and corresponding text file.
339
- Many of the 20217 recorded hours in the dataset also include demographic metadata like age, sex, and accent
340
- that can help improve the accuracy of speech recognition engines.
341
-
342
- The dataset currently consists of 14973 validated hours in 93 languages, but more voices and languages are always added.
343
- Take a look at the [Languages](https://commonvoice.mozilla.org/en/languages) page to request a language or start contributing.
344
-
345
- ### Supported Tasks and Leaderboards
346
-
347
- The results for models trained on the Common Voice datasets are available via the
348
- [Papers with Code Leaderboards](https://paperswithcode.com/dataset/common-voice)
349
-
350
- ### Languages
351
-
352
- ```
353
- Abkhaz, Arabic, Armenian, Assamese, Azerbaijani, Basaa, Bashkir, Basque, Belarusian, Bengali, Breton, Bulgarian, Cantonese, Catalan, Central Kurdish, Chinese (China), Chinese (Hong Kong), Chinese (Taiwan), Chuvash, Czech, Danish, Dhivehi, Dutch, English, Erzya, Esperanto, Estonian, Finnish, French, Frisian, Galician, Georgian, German, Greek, Guarani, Hakha Chin, Hausa, Hindi, Hungarian, Igbo, Indonesian, Interlingua, Irish, Italian, Japanese, Kabyle, Kazakh, Kinyarwanda, Kurmanji Kurdish, Kyrgyz, Latvian, Lithuanian, Luganda, Macedonian, Malayalam, Maltese, Marathi, Meadow Mari, Moksha, Mongolian, Norwegian Nynorsk, Odia, Persian, Polish, Portuguese, Punjabi, Romanian, Romansh Sursilvan, Romansh Vallader, Russian, Sakha, Santali (Ol Chiki), Serbian, Slovak, Slovenian, Sorbian, Upper, Spanish, Swahili, Swedish, Taiwanese (Minnan), Tamil, Tatar, Thai, Tigre, Toki Pona, Turkish, Ukrainian, Urdu, Uyghur, Uzbek, Vietnamese, Votic, Welsh
354
- ```
355
-
356
- ## Dataset Structure
357
-
358
- ### Data Instances
359
-
360
- A typical data point comprises the `path` to the audio file and its `sentence`.
361
- Additional fields include `accent`, `age`, `client_id`, `up_votes`, `down_votes`, `gender`, `locale` and `segment`.
362
-
363
- ```python
364
- {
365
- 'client_id': 'd59478fbc1ee646a28a3c652a119379939123784d99131b865a89f8b21c81f69276c48bd574b81267d9d1a77b83b43e6d475a6cfc79c232ddbca946ae9c7afc5',
366
- 'path': 'et/clips/common_voice_et_18318995.mp3',
367
- 'audio': {
368
- 'path': 'et/clips/common_voice_et_18318995.mp3',
369
- 'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, 0.00091553, 0.00085449], dtype=float32),
370
- 'sampling_rate': 48000
371
- },
372
- 'sentence': 'Tasub kokku saada inimestega, keda tunned juba ammust ajast saati.',
373
- 'up_votes': 2,
374
- 'down_votes': 0,
375
- 'age': 'twenties',
376
- 'gender': 'male',
377
- 'accent': '',
378
- 'locale': 'et',
379
- 'segment': ''
380
- }
381
- ```
382
-
383
- ### Data Fields
384
-
385
- `client_id` (`string`): An id for which client (voice) made the recording
386
-
387
- `path` (`string`): The path to the audio file
388
-
389
- `audio` (`dict`): A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`.
390
-
391
- `sentence` (`string`): The sentence the user was prompted to speak
392
-
393
- `up_votes` (`int64`): How many upvotes the audio file has received from reviewers
394
-
395
- `down_votes` (`int64`): How many downvotes the audio file has received from reviewers
396
-
397
- `age` (`string`): The age of the speaker (e.g. `teens`, `twenties`, `fifties`)
398
-
399
- `gender` (`string`): The gender of the speaker
400
-
401
- `accent` (`string`): Accent of the speaker
402
-
403
- `locale` (`string`): The locale of the speaker
404
-
405
- `segment` (`string`): Usually an empty field
406
-
407
- ### Data Splits
408
-
409
- The speech material has been subdivided into portions for dev, train, test, validated, invalidated, reported and other.
410
-
411
- The validated data is data that has been validated with reviewers and recieved upvotes that the data is of high quality.
412
-
413
- The invalidated data is data has been invalidated by reviewers
414
- and received downvotes indicating that the data is of low quality.
415
-
416
- The reported data is data that has been reported, for different reasons.
417
-
418
- The other data is data that has not yet been reviewed.
419
-
420
- The dev, test, train are all data that has been reviewed, deemed of high quality and split into dev, test and train.
421
-
422
-
423
- ## Data Preprocessing Recommended by Hugging Face
424
- The following are data preprocessing steps advised by the Hugging Face team. They are accompanied by an example code snippet that shows how to put them to practice.
425
-
426
- Many examples in this dataset have trailing quotations marks, e.g _“the cat sat on the mat.“_. These trailing quotation marks do not change the actual meaning of the sentence, and it is near impossible to infer whether a sentence is a quotation or not a quotation from audio data alone. In these cases, it is advised to strip the quotation marks, leaving: _the cat sat on the mat_.
427
-
428
- In addition, the majority of training sentences end in punctuation ( . or ? or ! ), whereas just a small proportion do not. In the dev set, **almost all** sentences end in punctuation. Thus, it is recommended to append a full-stop ( . ) to the end of the small number of training examples that do not end in punctuation.
429
-
430
- ```python
431
- from datasets import load_dataset
432
-
433
- ds = load_dataset("mozilla-foundation/common_voice_9_0", "en", use_auth_token=True)
434
-
435
- def prepare_dataset(batch):
436
- """Function to preprocess the dataset with the .map method"""
437
- transcription = batch["sentence"]
438
-
439
- if transcription.startswith('"') and transcription.endswith('"'):
440
- # we can remove trailing quotation marks as they do not affect the transcription
441
- transcription = transcription[1:-1]
442
-
443
- if transcription[-1] not in [".", "?", "!"]:
444
- # append a full-stop to sentences that do not end in punctuation
445
- transcription = transcription + "."
446
-
447
- batch["sentence"] = transcription
448
-
449
- return batch
450
-
451
- ds = ds.map(prepare_dataset, desc="preprocess dataset")
452
- ```
453
- ## Dataset Creation
454
-
455
- ### Curation Rationale
456
-
457
- [Needs More Information]
458
-
459
- ### Source Data
460
-
461
- #### Initial Data Collection and Normalization
462
-
463
- [Needs More Information]
464
-
465
- #### Who are the source language producers?
466
-
467
- [Needs More Information]
468
-
469
- ### Annotations
470
-
471
- #### Annotation process
472
-
473
- [Needs More Information]
474
-
475
- #### Who are the annotators?
476
-
477
- [Needs More Information]
478
-
479
- ### Personal and Sensitive Information
480
-
481
- The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in the Common Voice dataset.
482
-
483
- ## Considerations for Using the Data
484
-
485
- ### Social Impact of Dataset
486
-
487
- The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in the Common Voice dataset.
488
-
489
- ### Discussion of Biases
490
-
491
- [More Information Needed]
492
-
493
- ### Other Known Limitations
494
-
495
- [More Information Needed]
496
-
497
- ## Additional Information
498
-
499
- ### Dataset Curators
500
-
501
- [More Information Needed]
502
-
503
- ### Licensing Information
504
-
505
- Public Domain, [CC-0](https://creativecommons.org/share-your-work/public-domain/cc0/)
506
-
507
-
508
-
509
- ## How to download the dataset
510
 
511
  How to load the Common Voice Bangla dataset directly with the datasets library
512
 
@@ -514,18 +11,3 @@ Run
514
 
515
  1) from datasets import load_dataset
516
  2) dataset = load_dataset("bengaliAI/CommonVoiceBangla", "bn", delimiter='\t')
517
-
518
-
519
-
520
-
521
- ### Citation Information
522
-
523
- ```
524
- @inproceedings{commonvoice:2020,
525
- author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.},
526
- title = {Common Voice: A Massively-Multilingual Speech Corpus},
527
- booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)},
528
- pages = {4211--4215},
529
- year = 2020
530
- }
531
- ```
 
1
  ---
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+ license: cc0-1.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  How to load the Common Voice Bangla dataset directly with the datasets library
9
 
 
11
 
12
  1) from datasets import load_dataset
13
  2) dataset = load_dataset("bengaliAI/CommonVoiceBangla", "bn", delimiter='\t')
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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common_voice_bn.py CHANGED
@@ -96,7 +96,7 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
96
  "age": datasets.Value("string"),
97
  "gender": datasets.Value("string"),
98
  "accent": datasets.Value("string"),
99
- "locale": 'bn',
100
  "segment": datasets.Value("string"),
101
  }
102
  )
@@ -117,8 +117,7 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
117
 
118
  def _get_bundle_url(self, locale, url_template):
119
  # path = encodeURIComponent(path)
120
- # path = url_template.replace("{locale}", locale)
121
- path = url_template
122
  path = urllib.parse.quote(path.encode("utf-8"), safe="~()*!.'")
123
  # use_cdn = self.config.size_bytes < 20 * 1024 * 1024 * 1024
124
  # response = requests.get(f"{_API_URL}/bucket/dataset/{path}/{use_cdn}", timeout=10.0).json()
@@ -174,18 +173,21 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
174
  # if path_to_data
175
  # else "train.tsv",
176
  #custom train.tsv
177
- "metadata_filepath": "/".join([path_to_tsvs, "train.tsv"]) if path_to_tsvs else "train.tsv",
178
  "path_to_clips": path_to_clips,
179
  },
180
  ),
181
- datasets.SplitGenerator(
182
  name=datasets.Split.TEST,
183
  gen_kwargs={
184
  "local_extracted_archive": local_extracted_archive,
185
  "archive_iterator": dl_manager.iter_archive(archive_path),
186
- "metadata_filepath": "/".join([path_to_data, "test.tsv"]) if path_to_data else "test.tsv",
 
 
 
 
187
  "path_to_clips": path_to_clips,
188
- "mode":"test",
189
  },
190
  ),
191
  datasets.SplitGenerator(
@@ -193,40 +195,19 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
193
  gen_kwargs={
194
  "local_extracted_archive": local_extracted_archive,
195
  "archive_iterator": dl_manager.iter_archive(archive_path),
196
- "metadata_filepath": "/".join([path_to_data, "dev.tsv"]) if path_to_data else "dev.tsv",
 
 
 
 
197
  "path_to_clips": path_to_clips,
198
- "mode":"dev",
199
  },
200
  ),
201
- # datasets.SplitGenerator(
202
- # name=datasets.Split.TEST,
203
- # gen_kwargs={
204
- # "local_extracted_archive": local_extracted_archive,
205
- # "archive_iterator": dl_manager.iter_archive(archive_path),
206
- # #"metadata_filepath": "/".join([path_to_data, "test.tsv"])
207
- # # if path_to_data
208
- # # else "test.tsv",
209
- # #custom test.tsv
210
- # "metadata_filepath": "/".join([path_to_tsvs, "test.tsv"]),
211
- # "path_to_clips": path_to_clips,
212
- # },
213
- # ),
214
- # datasets.SplitGenerator(
215
- # name=datasets.Split.VALIDATION,
216
- # gen_kwargs={
217
- # "local_extracted_archive": local_extracted_archive,
218
- # "archive_iterator": dl_manager.iter_archive(archive_path),
219
- # # "metadata_filepath": "/".join([path_to_data, "dev.tsv"])
220
- # # if path_to_data
221
- # # else "dev.tsv",
222
- # #custom test.tsv
223
- # "metadata_filepath": "/".join([path_to_tsvs, "dev.tsv"]),
224
- # "path_to_clips": path_to_clips,
225
- # },
226
- # ),
227
  ]
228
 
229
- def _generate_examples(
 
 
230
  self,
231
  local_extracted_archive,
232
  archive_iterator,
@@ -236,27 +217,27 @@ def _generate_examples(
236
  """Yields examples."""
237
  data_fields = list(self._info().features.keys())
238
  metadata = {}
239
- metadata_found = True
240
- with open(metadata_filepath, "rb") as file_obj:
241
- lines = (line.decode("utf-8") for line in file_obj)
242
- #lines = (line.decode("utf-8") for line in f)
243
- reader = csv.DictReader(lines, delimiter="\t", quoting=csv.QUOTE_NONE)
244
- for row in reader:
245
- # set absolute path for mp3 audio file
246
- if not row["path"].endswith(".mp3"):
247
- row["path"] += ".mp3"
248
- row["path"] = os.path.join(path_to_clips, row["path"])
249
- # accent -> accents in CV 8.0
250
- if "accents" in row:
251
- row["accent"] = row["accents"]
252
- del row["accents"]
253
- # if data is incomplete, fill with empty values
254
- for field in data_fields:
255
- if field not in row:
256
- row[field] = ""
257
- metadata[row["path"]] = row
258
- for path, f in archive_iterator:
259
- if path.startswith(path_to_clips):
260
  assert metadata_found, "Found audio clips before the metadata TSV file."
261
  if not metadata:
262
  break
@@ -274,54 +255,6 @@ def _generate_examples(
274
 
275
  yield path, result
276
 
277
- # def _generate_examples(
278
- # self,
279
- # local_extracted_archive,
280
- # archive_iterator,
281
- # metadata_filepath,
282
- # path_to_clips,
283
- # ):
284
- # """Yields examples."""
285
- # data_fields = list(self._info().features.keys())
286
- # metadata = {}
287
- # metadata_found = False
288
- # for path, f in archive_iterator:
289
- # if path == metadata_filepath:
290
- # metadata_found = True
291
- # lines = (line.decode("utf-8") for line in f)
292
- # reader = csv.DictReader(lines, delimiter="\t", quoting=csv.QUOTE_NONE)
293
- # for row in reader:
294
- # # set absolute path for mp3 audio file
295
- # if not row["path"].endswith(".mp3"):
296
- # row["path"] += ".mp3"
297
- # row["path"] = os.path.join(path_to_clips, row["path"])
298
- # # accent -> accents in CV 8.0
299
- # if "accents" in row:
300
- # row["accent"] = row["accents"]
301
- # del row["accents"]
302
- # # if data is incomplete, fill with empty values
303
- # for field in data_fields:
304
- # if field not in row:
305
- # row[field] = ""
306
- # metadata[row["path"]] = row
307
- # elif path.startswith(path_to_clips):
308
- # assert metadata_found, "Found audio clips before the metadata TSV file."
309
- # if not metadata:
310
- # break
311
- # if path in metadata:
312
- # result = metadata[path]
313
- # # set the audio feature and the path to the extracted file
314
- # path = (
315
- # os.path.join(local_extracted_archive, path)
316
- # if local_extracted_archive
317
- # else path
318
- # )
319
- # result["audio"] = {"path": path, "bytes": f.read()}
320
- # # set path to None if the audio file doesn't exist locally (i.e. in streaming mode)
321
- # result["path"] = path if local_extracted_archive else None
322
-
323
- # yield path, result
324
-
325
 
326
 
327
  # 'bn': {'duration': 1438112808, 'reportedSentences': 693, 'buckets': {'dev': 7748, 'invalidated': 5844, 'other': 192522,
 
96
  "age": datasets.Value("string"),
97
  "gender": datasets.Value("string"),
98
  "accent": datasets.Value("string"),
99
+ "locale": datasets.Value("string"),
100
  "segment": datasets.Value("string"),
101
  }
102
  )
 
117
 
118
  def _get_bundle_url(self, locale, url_template):
119
  # path = encodeURIComponent(path)
120
+ path = url_template.replace("{locale}", locale)
 
121
  path = urllib.parse.quote(path.encode("utf-8"), safe="~()*!.'")
122
  # use_cdn = self.config.size_bytes < 20 * 1024 * 1024 * 1024
123
  # response = requests.get(f"{_API_URL}/bucket/dataset/{path}/{use_cdn}", timeout=10.0).json()
 
173
  # if path_to_data
174
  # else "train.tsv",
175
  #custom train.tsv
176
+ "metadata_filepath": "/".join([path_to_tsvs, "train.tsv"]),
177
  "path_to_clips": path_to_clips,
178
  },
179
  ),
180
+ datasets.SplitGenerator(
181
  name=datasets.Split.TEST,
182
  gen_kwargs={
183
  "local_extracted_archive": local_extracted_archive,
184
  "archive_iterator": dl_manager.iter_archive(archive_path),
185
+ #"metadata_filepath": "/".join([path_to_data, "test.tsv"])
186
+ # if path_to_data
187
+ # else "test.tsv",
188
+ #custom test.tsv
189
+ "metadata_filepath": "/".join([path_to_tsvs, "test.tsv"]),
190
  "path_to_clips": path_to_clips,
 
191
  },
192
  ),
193
  datasets.SplitGenerator(
 
195
  gen_kwargs={
196
  "local_extracted_archive": local_extracted_archive,
197
  "archive_iterator": dl_manager.iter_archive(archive_path),
198
+ # "metadata_filepath": "/".join([path_to_data, "dev.tsv"])
199
+ # if path_to_data
200
+ # else "dev.tsv",
201
+ #custom test.tsv
202
+ "metadata_filepath": "/".join([path_to_tsvs, "dev.tsv"]),
203
  "path_to_clips": path_to_clips,
 
204
  },
205
  ),
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
206
  ]
207
 
208
+
209
+
210
+ def _generate_examples(
211
  self,
212
  local_extracted_archive,
213
  archive_iterator,
 
217
  """Yields examples."""
218
  data_fields = list(self._info().features.keys())
219
  metadata = {}
220
+ metadata_found = False
221
+ for path, f in archive_iterator:
222
+ if path == metadata_filepath:
223
+ metadata_found = True
224
+ lines = (line.decode("utf-8") for line in f)
225
+ reader = csv.DictReader(lines, delimiter="\t", quoting=csv.QUOTE_NONE)
226
+ for row in reader:
227
+ # set absolute path for mp3 audio file
228
+ if not row["path"].endswith(".mp3"):
229
+ row["path"] += ".mp3"
230
+ row["path"] = os.path.join(path_to_clips, row["path"])
231
+ # accent -> accents in CV 8.0
232
+ if "accents" in row:
233
+ row["accent"] = row["accents"]
234
+ del row["accents"]
235
+ # if data is incomplete, fill with empty values
236
+ for field in data_fields:
237
+ if field not in row:
238
+ row[field] = ""
239
+ metadata[row["path"]] = row
240
+ elif path.startswith(path_to_clips):
241
  assert metadata_found, "Found audio clips before the metadata TSV file."
242
  if not metadata:
243
  break
 
255
 
256
  yield path, result
257
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
258
 
259
 
260
  # 'bn': {'duration': 1438112808, 'reportedSentences': 693, 'buckets': {'dev': 7748, 'invalidated': 5844, 'other': 192522,
languages.py CHANGED
@@ -1 +1 @@
1
- LANGUAGES = { 'bn': 'Bengali'}
 
1
+ LANGUAGES = {"bn": "Bengali"}
release_stats.py CHANGED
@@ -1,45 +1 @@
1
- STATS = {
2
- "bundleURLTemplate": "cv-corpus-9.0-2022-04-27/cv-corpus-9.0-2022-04-27-bn.tar.gz",
3
- "date": "2022-04-27",
4
- "name": "Common Voice Corpus 9.0",
5
- "multilingual": True,
6
- "locales": {
7
- "bn": {
8
- "duration": 1438112808,
9
- "reportedSentences": 693,
10
- "buckets": {
11
- "dev": 7748,
12
- "invalidated": 5844,
13
- "other": 192522,
14
- "reported": 717,
15
- "test": 7748,
16
- "train": 14503,
17
- "validated": 32754,
18
- },
19
- "clips": 231120,
20
- "splits": {
21
- "accent": {"": 1},
22
- "age": {
23
- "thirties": 0.02,
24
- "twenties": 0.22,
25
- "": 0.72,
26
- "teens": 0.04,
27
- "fourties": 0,
28
- },
29
- "gender": {"male": 0.24, "": 0.72, "female": 0.04, "other": 0},
30
- },
31
- "users": 19863,
32
- "size": 8262390506,
33
- "checksum": "599a5f7c9e55a297928da390345a19180b279a1f013081e7255a657fc99f98d5",
34
- "avgDurationSecs": 6.222,
35
- "validDurationSecs": 203807.316,
36
- "totalHrs": 399.47,
37
- "validHrs": 56.61,
38
- }
39
- },
40
- "totalDuration": 72782088097,
41
- "totalValidDurationSecs": 53904443,
42
- "totalHrs": 20217,
43
- "totalValidHrs": 14973,
44
- "version": "9.0.0",
45
- }
 
1
+ STATS = {'bundleURLTemplate': 'cv-corpus-9.0-2022-04-27/cv-corpus-9.0-2022-04-27-{locale}.tar.gz', 'date': '2022-04-27', 'name': 'Common Voice Corpus 9.0', 'multilingual': True, 'locales': {'en': {'duration': 10632910099, 'buckets': {'dev': 16335, 'invalidated': 242945, 'other': 267228, 'reported': 3903, 'test': 16335, 'train': 890116, 'validated': 1556254}, 'reportedSentences': 3842, 'clips': 2066427, 'splits': {'accent': {'': 1}, 'age': {'': 0.37, 'twenties': 0.24, 'sixties': 0.04, 'thirties': 0.13, 'teens': 0.06, 'seventies': 0.01, 'fourties': 0.1, 'fifties': 0.05, 'eighties': 0, 'nineties': 0}, 'gender': {'': 0.37, 'male': 0.46, 'female': 0.15, 'other': 0.02}}, 'users': 81085, 'size': 76768058135, 'checksum': '7c789a325e1d9f16137c1aeab9f45a1fde049a39b8fbf49e9ef4a8827ae67eae', 'avgDurationSecs': 5.146, 'validDurationSecs': 8007787.777, 'totalHrs': 2953.58, 'validHrs': 2224.38}, 'eu': {'reportedSentences': 44, 'buckets': {'dev': 6558, 'invalidated': 5785, 'other': 26668, 'reported': 43, 'test': 6558, 'train': 10825, 'validated': 69111}, 'duration': 527089551, 'clips': 101564, 'splits': {'accent': {'': 1}, 'age': {'fourties': 0.13, 'thirties': 0.07, 'fifties': 0.14, 'twenties': 0.35, '': 0.25, 'teens': 0.03, 'sixties': 0.02, 'seventies': 0}, 'gender': {'male': 0.47, 'female': 0.26, '': 0.25, 'other': 0.02}}, 'users': 1201, 'size': 3975713611, 'checksum': 'd28b239b95019469c3fa3a64587906efac9e152f2cb4a19d3175d9fa7f4f2e18', 'avgDurationSecs': 5.19, 'validDurationSecs': 358667.303, 'totalHrs': 146.41, 'validHrs': 99.62}, 'tr': {'reportedSentences': 306, 'buckets': {'dev': 8313, 'invalidated': 3262, 'other': 151, 'reported': 305, 'test': 8362, 'train': 16862, 'validated': 66078}, 'duration': 256673727, 'clips': 69491, 'splits': {'accent': {'': 1}, 'age': {'': 0.33, 'thirties': 0.1, 'twenties': 0.28, 'teens': 0.02, 'fourties': 0.04, 'fifties': 0.09, 'sixties': 0.09, 'eighties': 0, 'seventies': 0.04}, 'gender': {'': 0.33, 'male': 0.46, 'female': 0.2, 'other': 0}}, 'users': 1264, 'size': 1608944247, 'checksum': '7064e9f756fb93b4d0c1b0dae619280d3470c5e95cb7e5406953ac4888dbd8d7', 'avgDurationSecs': 3.694, 'validDurationSecs': 244067.383, 'totalHrs': 71.29, 'validHrs': 67.79}, 'ar': {'reportedSentences': 2033, 'buckets': {'dev': 10220, 'invalidated': 14873, 'other': 30302, 'reported': 2040, 'test': 10421, 'train': 28139, 'validated': 75322}, 'duration': 502349703, 'clips': 120497, 'splits': {'accent': {'': 1}, 'age': {'thirties': 0.12, '': 0.58, 'twenties': 0.26, 'fourties': 0.01, 'teens': 0.03, 'fifties': 0, 'sixties': 0, 'nineties': 0}, 'gender': {'female': 0.17, '': 0.57, 'male': 0.25, 'other': 0}}, 'users': 1237, 'size': 2995697303, 'checksum': 'd29c81a1801ba01af97b7a90548dfd0409b9efa9b9d1291e28deee90267a746b', 'avgDurationSecs': 4.169, 'validDurationSecs': 314017, 'totalHrs': 139.54, 'validHrs': 87.23}, 'zh-TW': {'reportedSentences': 139, 'buckets': {'dev': 4618, 'invalidated': 4482, 'other': 37593, 'reported': 138, 'test': 4618, 'train': 6393, 'validated': 74894}, 'duration': 380039242, 'clips': 116969, 'splits': {'accent': {'': 1}, 'age': {'thirties': 0.2, 'twenties': 0.33, 'teens': 0.05, '': 0.28, 'fifties': 0.04, 'seventies': 0, 'fourties': 0.1, 'sixties': 0}, 'gender': {'male': 0.46, '': 0.27, 'female': 0.25, 'other': 0.02}}, 'users': 2002, 'size': 2719746719, 'checksum': 'b40023ca8f5113a3766ba2d0844c3e846ff48eb1d4408d9ae912d4f9caa183eb', 'avgDurationSecs': 3.249, 'validDurationSecs': 243335.063, 'totalHrs': 105.56, 'validHrs': 67.59}, 'br': {'duration': 71324827, 'reportedSentences': 183, 'buckets': {'dev': 2161, 'invalidated': 756, 'other': 11283, 'reported': 182, 'test': 2150, 'train': 2561, 'validated': 11152}, 'clips': 23191, 'splits': {'accent': {'': 1}, 'age': {'twenties': 0.25, '': 0.33, 'fifties': 0.06, 'fourties': 0.07, 'thirties': 0.08, 'sixties': 0.18, 'seventies': 0.02, 'teens': 0.01}, 'gender': {'male': 0.65, '': 0.34, 'female': 0.02}}, 'users': 172, 'size': 525880271, 'checksum': '7a49666d12df795d95c5d64e827970e40863f26dfb87ceae61d14819788e6cfa', 'avgDurationSecs': 3.076, 'validDurationSecs': 34298.412, 'totalHrs': 19.81, 'validHrs': 9.52}, 'pt': {'duration': 484853047, 'reportedSentences': 2305, 'buckets': {'dev': 8528, 'invalidated': 4416, 'other': 11900, 'reported': 2310, 'test': 8539, 'train': 17559, 'validated': 99173}, 'clips': 115489, 'splits': {'accent': {'': 1}, 'age': {'': 0.2, 'twenties': 0.42, 'teens': 0.03, 'thirties': 0.22, 'fourties': 0.1, 'sixties': 0, 'fifties': 0.03, 'seventies': 0}, 'gender': {'': 0.2, 'male': 0.74, 'female': 0.04, 'other': 0.02}}, 'users': 2453, 'size': 3187978215, 'checksum': '1a748f21ba194d57ecd6418cce9692a198eeabcb44ba6e2b7a34435efc6625a4', 'avgDurationSecs': 4.198, 'validDurationSecs': 416354.209, 'totalHrs': 134.68, 'validHrs': 115.65}, 'eo': {'duration': 6712729612, 'reportedSentences': 2113, 'buckets': {'dev': 14911, 'invalidated': 127285, 'other': 130550, 'reported': 2115, 'test': 14915, 'train': 143973, 'validated': 848434}, 'clips': 1106269, 'splits': {'accent': {'': 1}, 'age': {'twenties': 0.57, 'thirties': 0.12, '': 0.19, 'fourties': 0.04, 'fifties': 0.02, 'seventies': 0, 'teens': 0.05, 'sixties': 0, 'eighties': 0}, 'gender': {'male': 0.69, '': 0.2, 'female': 0.11, 'other': 0}}, 'users': 1498, 'size': 40086922305, 'checksum': '5b341a961cf9f680d5c97d0be4f817fedbdfe695a3cf18825363c4c9104899b7', 'avgDurationSecs': 6.068, 'validDurationSecs': 5148297, 'totalHrs': 1864.65, 'validHrs': 1430.08}, 'zh-CN': {'reportedSentences': 445, 'buckets': {'dev': 9740, 'invalidated': 6689, 'other': 14066, 'reported': 458, 'test': 9747, 'train': 23539, 'validated': 48516}, 'duration': 358872900, 'clips': 69271, 'splits': {'accent': {'': 1}, 'age': {'': 0.39, 'teens': 0.09, 'twenties': 0.38, 'thirties': 0.11, 'fourties': 0.03, 'nineties': 0, 'fifties': 0, 'sixties': 0}, 'gender': {'': 0.39, 'male': 0.51, 'female': 0.1, 'other': 0.01}}, 'users': 4233, 'size': 2637465454, 'checksum': 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