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Release 11.0

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  1. README.md +539 -0
  2. common_voice_11_0.py +260 -0
  3. languages.py +1 -0
  4. release_stats.py +1 -0
README.md ADDED
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+ ---
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+ pretty_name: Common Voice Corpus 11.0
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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:
316
+ - speech-processing
317
+ task_ids:
318
+ - automatic-speech-recognition
319
+ 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."
321
+ ---
322
+
323
+ # Dataset Card for Common Voice Corpus 11.0
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+
325
+ ## Table of Contents
326
+ - [Dataset Description](#dataset-description)
327
+ - [Dataset Summary](#dataset-summary)
328
+ - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
329
+ - [Languages](#languages)
330
+ - [Dataset Structure](#dataset-structure)
331
+ - [Data Instances](#data-instances)
332
+ - [Data Fields](#data-fields)
333
+ - [Data Splits](#data-splits)
334
+ - [Dataset Creation](#dataset-creation)
335
+ - [Curation Rationale](#curation-rationale)
336
+ - [Source Data](#source-data)
337
+ - [Annotations](#annotations)
338
+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
339
+ - [Considerations for Using the Data](#considerations-for-using-the-data)
340
+ - [Social Impact of Dataset](#social-impact-of-dataset)
341
+ - [Discussion of Biases](#discussion-of-biases)
342
+ - [Other Known Limitations](#other-known-limitations)
343
+ - [Additional Information](#additional-information)
344
+ - [Dataset Curators](#dataset-curators)
345
+ - [Licensing Information](#licensing-information)
346
+ - [Citation Information](#citation-information)
347
+ - [Contributions](#contributions)
348
+
349
+ ## Dataset Description
350
+
351
+ - **Homepage:** https://commonvoice.mozilla.org/en/datasets
352
+ - **Repository:** https://github.com/common-voice/common-voice
353
+ - **Paper:** https://arxiv.org/abs/1912.06670
354
+ - **Leaderboard:** https://paperswithcode.com/dataset/common-voice
355
+ - **Point of Contact:** [Anton Lozhkov](mailto:anton@huggingface.co)
356
+
357
+ ### Dataset Summary
358
+
359
+ The Common Voice dataset consists of a unique MP3 and corresponding text file.
360
+ Many of the 24210 recorded hours in the dataset also include demographic metadata like age, sex, and accent
361
+ that can help improve the accuracy of speech recognition engines.
362
+
363
+ The dataset currently consists of 16413 validated hours in 100 languages, but more voices and languages are always added.
364
+ Take a look at the [Languages](https://commonvoice.mozilla.org/en/languages) page to request a language or start contributing.
365
+
366
+ ### Supported Tasks and Leaderboards
367
+
368
+ The results for models trained on the Common Voice datasets are available via the
369
+ [🤗 Speech Bench](https://huggingface.co/spaces/huggingface/hf-speech-bench)
370
+
371
+ ### Languages
372
+
373
+ ```
374
+ Abkhaz, Arabic, Armenian, Assamese, Asturian, 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, Hill Mari, 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, Nepali, Norwegian Nynorsk, Odia, Persian, Polish, Portuguese, Punjabi, Romanian, Romansh Sursilvan, Romansh Vallader, Russian, Sakha, Santali (Ol Chiki), Saraiki, Sardinian, Serbian, Slovak, Slovenian, Sorbian, Upper, Spanish, Swahili, Swedish, Taiwanese (Minnan), Tamil, Tatar, Thai, Tigre, Tigrinya, Toki Pona, Turkish, Twi, Ukrainian, Urdu, Uyghur, Uzbek, Vietnamese, Votic, Welsh
375
+ ```
376
+
377
+ ## Dataset Structure
378
+
379
+ ### Data Instances
380
+
381
+ A typical data point comprises the `path` to the audio file and its `sentence`.
382
+ Additional fields include `accent`, `age`, `client_id`, `up_votes`, `down_votes`, `gender`, `locale` and `segment`.
383
+
384
+ ```python
385
+ {
386
+ 'client_id': 'd59478fbc1ee646a28a3c652a119379939123784d99131b865a89f8b21c81f69276c48bd574b81267d9d1a77b83b43e6d475a6cfc79c232ddbca946ae9c7afc5',
387
+ 'path': 'et/clips/common_voice_et_18318995.mp3',
388
+ 'audio': {
389
+ 'path': 'et/clips/common_voice_et_18318995.mp3',
390
+ 'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, 0.00091553, 0.00085449], dtype=float32),
391
+ 'sampling_rate': 48000
392
+ },
393
+ 'sentence': 'Tasub kokku saada inimestega, keda tunned juba ammust ajast saati.',
394
+ 'up_votes': 2,
395
+ 'down_votes': 0,
396
+ 'age': 'twenties',
397
+ 'gender': 'male',
398
+ 'accent': '',
399
+ 'locale': 'et',
400
+ 'segment': ''
401
+ }
402
+ ```
403
+
404
+ ### Data Fields
405
+
406
+ `client_id` (`string`): An id for which client (voice) made the recording
407
+
408
+ `path` (`string`): The path to the audio file
409
+
410
+ `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]`.
411
+
412
+ `sentence` (`string`): The sentence the user was prompted to speak
413
+
414
+ `up_votes` (`int64`): How many upvotes the audio file has received from reviewers
415
+
416
+ `down_votes` (`int64`): How many downvotes the audio file has received from reviewers
417
+
418
+ `age` (`string`): The age of the speaker (e.g. `teens`, `twenties`, `fifties`)
419
+
420
+ `gender` (`string`): The gender of the speaker
421
+
422
+ `accent` (`string`): Accent of the speaker
423
+
424
+ `locale` (`string`): The locale of the speaker
425
+
426
+ `segment` (`string`): Usually an empty field
427
+
428
+ ### Data Splits
429
+
430
+ The speech material has been subdivided into portions for dev, train, test, validated, invalidated, reported and other.
431
+
432
+ The validated data is data that has been validated with reviewers and received upvotes that the data is of high quality.
433
+
434
+ The invalidated data is data has been invalidated by reviewers
435
+ and received downvotes indicating that the data is of low quality.
436
+
437
+ The reported data is data that has been reported, for different reasons.
438
+
439
+ The other data is data that has not yet been reviewed.
440
+
441
+ The dev, test, train are all data that has been reviewed, deemed of high quality and split into dev, test and train.
442
+
443
+ ## Data Preprocessing Recommended by Hugging Face
444
+
445
+ 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.
446
+
447
+ 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_.
448
+
449
+ 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.
450
+
451
+ ```python
452
+ from datasets import load_dataset
453
+
454
+ ds = load_dataset("mozilla-foundation/common_voice_11_0", "en", use_auth_token=True)
455
+
456
+ def prepare_dataset(batch):
457
+ """Function to preprocess the dataset with the .map method"""
458
+ transcription = batch["sentence"]
459
+
460
+ if transcription.startswith('"') and transcription.endswith('"'):
461
+ # we can remove trailing quotation marks as they do not affect the transcription
462
+ transcription = transcription[1:-1]
463
+
464
+ if transcription[-1] not in [".", "?", "!"]:
465
+ # append a full-stop to sentences that do not end in punctuation
466
+ transcription = transcription + "."
467
+
468
+ batch["sentence"] = transcription
469
+
470
+ return batch
471
+
472
+ ds = ds.map(prepare_dataset, desc="preprocess dataset")
473
+ ```
474
+
475
+ ## Dataset Creation
476
+
477
+ ### Curation Rationale
478
+
479
+ [Needs More Information]
480
+
481
+ ### Source Data
482
+
483
+ #### Initial Data Collection and Normalization
484
+
485
+ [Needs More Information]
486
+
487
+ #### Who are the source language producers?
488
+
489
+ [Needs More Information]
490
+
491
+ ### Annotations
492
+
493
+ #### Annotation process
494
+
495
+ [Needs More Information]
496
+
497
+ #### Who are the annotators?
498
+
499
+ [Needs More Information]
500
+
501
+ ### Personal and Sensitive Information
502
+
503
+ 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.
504
+
505
+ ## Considerations for Using the Data
506
+
507
+ ### Social Impact of Dataset
508
+
509
+ 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.
510
+
511
+ ### Discussion of Biases
512
+
513
+ [More Information Needed]
514
+
515
+ ### Other Known Limitations
516
+
517
+ [More Information Needed]
518
+
519
+ ## Additional Information
520
+
521
+ ### Dataset Curators
522
+
523
+ [More Information Needed]
524
+
525
+ ### Licensing Information
526
+
527
+ Public Domain, [CC-0](https://creativecommons.org/share-your-work/public-domain/cc0/)
528
+
529
+ ### Citation Information
530
+
531
+ ```
532
+ @inproceedings{commonvoice:2020,
533
+ 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.},
534
+ title = {Common Voice: A Massively-Multilingual Speech Corpus},
535
+ booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)},
536
+ pages = {4211--4215},
537
+ year = 2020
538
+ }
539
+ ```
common_voice_11_0.py ADDED
@@ -0,0 +1,260 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # coding=utf-8
2
+ # Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
3
+ #
4
+ # Licensed under the Apache License, Version 2.0 (the "License");
5
+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+ """ Common Voice Dataset"""
16
+
17
+
18
+ import csv
19
+ import os
20
+ import urllib
21
+
22
+ import datasets
23
+ import requests
24
+ from datasets.utils.py_utils import size_str
25
+ from huggingface_hub import HfApi, HfFolder
26
+
27
+ from .languages import LANGUAGES
28
+ from .release_stats import STATS
29
+
30
+ _CITATION = """\
31
+ @inproceedings{commonvoice:2020,
32
+ 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.},
33
+ title = {Common Voice: A Massively-Multilingual Speech Corpus},
34
+ booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)},
35
+ pages = {4211--4215},
36
+ year = 2020
37
+ }
38
+ """
39
+
40
+ _HOMEPAGE = "https://commonvoice.mozilla.org/en/datasets"
41
+
42
+ _LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
43
+
44
+ _API_URL = "https://commonvoice.mozilla.org/api/v1"
45
+
46
+
47
+ class CommonVoiceConfig(datasets.BuilderConfig):
48
+ """BuilderConfig for CommonVoice."""
49
+
50
+ def __init__(self, name, version, **kwargs):
51
+ self.language = kwargs.pop("language", None)
52
+ self.release_date = kwargs.pop("release_date", None)
53
+ self.num_clips = kwargs.pop("num_clips", None)
54
+ self.num_speakers = kwargs.pop("num_speakers", None)
55
+ self.validated_hr = kwargs.pop("validated_hr", None)
56
+ self.total_hr = kwargs.pop("total_hr", None)
57
+ self.size_bytes = kwargs.pop("size_bytes", None)
58
+ self.size_human = size_str(self.size_bytes)
59
+ description = (
60
+ f"Common Voice speech to text dataset in {self.language} released on {self.release_date}. "
61
+ f"The dataset comprises {self.validated_hr} hours of validated transcribed speech data "
62
+ f"out of {self.total_hr} hours in total from {self.num_speakers} speakers. "
63
+ f"The dataset contains {self.num_clips} audio clips and has a size of {self.size_human}."
64
+ )
65
+ super(CommonVoiceConfig, self).__init__(
66
+ name=name,
67
+ version=datasets.Version(version),
68
+ description=description,
69
+ **kwargs,
70
+ )
71
+
72
+
73
+ class CommonVoice(datasets.GeneratorBasedBuilder):
74
+ DEFAULT_CONFIG_NAME = "en"
75
+ DEFAULT_WRITER_BATCH_SIZE = 1000
76
+
77
+ BUILDER_CONFIGS = [
78
+ CommonVoiceConfig(
79
+ name=lang,
80
+ version=STATS["version"],
81
+ language=LANGUAGES[lang],
82
+ release_date=STATS["date"],
83
+ num_clips=lang_stats["clips"],
84
+ num_speakers=lang_stats["users"],
85
+ validated_hr=float(lang_stats["validHrs"]) if lang_stats["validHrs"] else None,
86
+ total_hr=float(lang_stats["totalHrs"]) if lang_stats["totalHrs"] else None,
87
+ size_bytes=int(lang_stats["size"]) if lang_stats["size"] else None,
88
+ )
89
+ for lang, lang_stats in STATS["locales"].items()
90
+ ]
91
+
92
+ def _info(self):
93
+ total_languages = len(STATS["locales"])
94
+ total_valid_hours = STATS["totalValidHrs"]
95
+ description = (
96
+ "Common Voice is Mozilla's initiative to help teach machines how real people speak. "
97
+ f"The dataset currently consists of {total_valid_hours} validated hours of speech "
98
+ f" in {total_languages} languages, but more voices and languages are always added."
99
+ )
100
+ features = datasets.Features(
101
+ {
102
+ "client_id": datasets.Value("string"),
103
+ "path": datasets.Value("string"),
104
+ "audio": datasets.features.Audio(sampling_rate=48_000),
105
+ "sentence": datasets.Value("string"),
106
+ "up_votes": datasets.Value("int64"),
107
+ "down_votes": datasets.Value("int64"),
108
+ "age": datasets.Value("string"),
109
+ "gender": datasets.Value("string"),
110
+ "accent": datasets.Value("string"),
111
+ "locale": datasets.Value("string"),
112
+ "segment": datasets.Value("string"),
113
+ }
114
+ )
115
+
116
+ return datasets.DatasetInfo(
117
+ description=description,
118
+ features=features,
119
+ supervised_keys=None,
120
+ homepage=_HOMEPAGE,
121
+ license=_LICENSE,
122
+ citation=_CITATION,
123
+ version=self.config.version,
124
+ # task_templates=[
125
+ # AutomaticSpeechRecognition(audio_file_path_column="path", transcription_column="sentence")
126
+ # ],
127
+ )
128
+
129
+ def _get_bundle_url(self, locale, url_template):
130
+ # path = encodeURIComponent(path)
131
+ path = url_template.replace("{locale}", locale)
132
+ path = urllib.parse.quote(path.encode("utf-8"), safe="~()*!.'")
133
+ # use_cdn = self.config.size_bytes < 20 * 1024 * 1024 * 1024
134
+ # response = requests.get(f"{_API_URL}/bucket/dataset/{path}/{use_cdn}", timeout=10.0).json()
135
+ response = requests.get(f"{_API_URL}/bucket/dataset/{path}", timeout=10.0).json()
136
+ return response["url"]
137
+
138
+ def _log_download(self, locale, bundle_version, auth_token):
139
+ if isinstance(auth_token, bool):
140
+ auth_token = HfFolder().get_token()
141
+ whoami = HfApi().whoami(auth_token)
142
+ email = whoami["email"] if "email" in whoami else ""
143
+ payload = {"email": email, "locale": locale, "dataset": bundle_version}
144
+ requests.post(f"{_API_URL}/{locale}/downloaders", json=payload).json()
145
+
146
+ def _split_generators(self, dl_manager):
147
+ """Returns SplitGenerators."""
148
+ hf_auth_token = dl_manager.download_config.use_auth_token
149
+ if hf_auth_token is None:
150
+ raise ConnectionError(
151
+ "Please set use_auth_token=True or use_auth_token='<TOKEN>' to download this dataset"
152
+ )
153
+
154
+ bundle_url_template = STATS["bundleURLTemplate"]
155
+ bundle_version = bundle_url_template.split("/")[0]
156
+ dl_manager.download_config.ignore_url_params = True
157
+
158
+ self._log_download(self.config.name, bundle_version, hf_auth_token)
159
+ archive_path = dl_manager.download(self._get_bundle_url(self.config.name, bundle_url_template))
160
+ local_extracted_archive = dl_manager.extract(archive_path) if not dl_manager.is_streaming else None
161
+
162
+ if self.config.version < datasets.Version("5.0.0"):
163
+ path_to_data = ""
164
+ else:
165
+ path_to_data = "/".join([bundle_version, self.config.name])
166
+ path_to_clips = "/".join([path_to_data, "clips"]) if path_to_data else "clips"
167
+
168
+ return [
169
+ datasets.SplitGenerator(
170
+ name=datasets.Split.TRAIN,
171
+ gen_kwargs={
172
+ "local_extracted_archive": local_extracted_archive,
173
+ "archive_iterator": dl_manager.iter_archive(archive_path),
174
+ "metadata_filepath": "/".join([path_to_data, "train.tsv"]) if path_to_data else "train.tsv",
175
+ "path_to_clips": path_to_clips,
176
+ },
177
+ ),
178
+ datasets.SplitGenerator(
179
+ name=datasets.Split.TEST,
180
+ gen_kwargs={
181
+ "local_extracted_archive": local_extracted_archive,
182
+ "archive_iterator": dl_manager.iter_archive(archive_path),
183
+ "metadata_filepath": "/".join([path_to_data, "test.tsv"]) if path_to_data else "test.tsv",
184
+ "path_to_clips": path_to_clips,
185
+ },
186
+ ),
187
+ datasets.SplitGenerator(
188
+ name=datasets.Split.VALIDATION,
189
+ gen_kwargs={
190
+ "local_extracted_archive": local_extracted_archive,
191
+ "archive_iterator": dl_manager.iter_archive(archive_path),
192
+ "metadata_filepath": "/".join([path_to_data, "dev.tsv"]) if path_to_data else "dev.tsv",
193
+ "path_to_clips": path_to_clips,
194
+ },
195
+ ),
196
+ datasets.SplitGenerator(
197
+ name="other",
198
+ gen_kwargs={
199
+ "local_extracted_archive": local_extracted_archive,
200
+ "archive_iterator": dl_manager.iter_archive(archive_path),
201
+ "metadata_filepath": "/".join([path_to_data, "other.tsv"]) if path_to_data else "other.tsv",
202
+ "path_to_clips": path_to_clips,
203
+ },
204
+ ),
205
+ datasets.SplitGenerator(
206
+ name="invalidated",
207
+ gen_kwargs={
208
+ "local_extracted_archive": local_extracted_archive,
209
+ "archive_iterator": dl_manager.iter_archive(archive_path),
210
+ "metadata_filepath": "/".join([path_to_data, "invalidated.tsv"])
211
+ if path_to_data
212
+ else "invalidated.tsv",
213
+ "path_to_clips": path_to_clips,
214
+ },
215
+ ),
216
+ ]
217
+
218
+ def _generate_examples(
219
+ self,
220
+ local_extracted_archive,
221
+ archive_iterator,
222
+ metadata_filepath,
223
+ path_to_clips,
224
+ ):
225
+ """Yields examples."""
226
+ data_fields = list(self._info().features.keys())
227
+ metadata = {}
228
+ metadata_found = False
229
+ for path, f in archive_iterator:
230
+ if path == metadata_filepath:
231
+ metadata_found = True
232
+ lines = (line.decode("utf-8") for line in f)
233
+ reader = csv.DictReader(lines, delimiter="\t", quoting=csv.QUOTE_NONE)
234
+ for row in reader:
235
+ # set absolute path for mp3 audio file
236
+ if not row["path"].endswith(".mp3"):
237
+ row["path"] += ".mp3"
238
+ row["path"] = os.path.join(path_to_clips, row["path"])
239
+ # accent -> accents in CV 8.0
240
+ if "accents" in row:
241
+ row["accent"] = row["accents"]
242
+ del row["accents"]
243
+ # if data is incomplete, fill with empty values
244
+ for field in data_fields:
245
+ if field not in row:
246
+ row[field] = ""
247
+ metadata[row["path"]] = row
248
+ elif path.startswith(path_to_clips):
249
+ assert metadata_found, "Found audio clips before the metadata TSV file."
250
+ if not metadata:
251
+ break
252
+ if path in metadata:
253
+ result = dict(metadata[path])
254
+ # set the audio feature and the path to the extracted file
255
+ path = os.path.join(local_extracted_archive, path) if local_extracted_archive else path
256
+ result["audio"] = {"path": path, "bytes": f.read()}
257
+ # set path to None if the audio file doesn't exist locally (i.e. in streaming mode)
258
+ result["path"] = path if local_extracted_archive else None
259
+
260
+ yield path, result
languages.py ADDED
@@ -0,0 +1 @@
 
 
1
+ LANGUAGES = {'ab': 'Abkhaz', 'ace': 'Acehnese', 'ady': 'Adyghe', 'af': 'Afrikaans', 'am': 'Amharic', 'an': 'Aragonese', 'ar': 'Arabic', 'arn': 'Mapudungun', 'as': 'Assamese', 'ast': 'Asturian', 'az': 'Azerbaijani', 'ba': 'Bashkir', 'bas': 'Basaa', 'be': 'Belarusian', 'bg': 'Bulgarian', 'bn': 'Bengali', 'br': 'Breton', 'bs': 'Bosnian', 'bxr': 'Buryat', 'ca': 'Catalan', 'cak': 'Kaqchikel', 'ckb': 'Central Kurdish', 'cnh': 'Hakha Chin', 'co': 'Corsican', 'cs': 'Czech', 'cv': 'Chuvash', 'cy': 'Welsh', 'da': 'Danish', 'de': 'German', 'dsb': 'Sorbian, Lower', 'dv': 'Dhivehi', 'dyu': 'Dioula', 'el': 'Greek', 'en': 'English', 'eo': 'Esperanto', 'es': 'Spanish', 'et': 'Estonian', 'eu': 'Basque', 'fa': 'Persian', 'ff': 'Fulah', 'fi': 'Finnish', 'fo': 'Faroese', 'fr': 'French', 'fy-NL': 'Frisian', 'ga-IE': 'Irish', 'gl': 'Galician', 'gn': 'Guarani', 'gom': 'Goan Konkani', 'ha': 'Hausa', 'he': 'Hebrew', 'hi': 'Hindi', 'hil': 'Hiligaynon', 'hr': 'Croatian', 'hsb': 'Sorbian, Upper', 'ht': 'Haitian', 'hu': 'Hungarian', 'hy-AM': 'Armenian', 'hyw': 'Armenian Western', 'ia': 'Interlingua', 'id': 'Indonesian', 'ie': 'Interlingue', 'ig': 'Igbo', 'is': 'Icelandic', 'it': 'Italian', 'izh': 'Izhorian', 'ja': 'Japanese', 'jbo': 'Lojban', 'ka': 'Georgian', 'kaa': 'Karakalpak', 'kab': 'Kabyle', 'kbd': 'Kabardian', 'ki': 'Kikuyu', 'kk': 'Kazakh', 'km': 'Khmer', 'kmr': 'Kurmanji Kurdish', 'kn': 'Kannada', 'knn': 'Konkani (Devanagari)', 'ko': 'Korean', 'kpv': 'Komi-Zyrian', 'kw': 'Cornish', 'ky': 'Kyrgyz', 'lb': 'Luxembourgish', 'lg': 'Luganda', 'lij': 'Ligurian', 'ln': 'Lingala', 'lo': 'Lao', 'lt': 'Lithuanian', 'lv': 'Latvian', 'mai': 'Maithili', 'mdf': 'Moksha', 'mg': 'Malagasy', 'mhr': 'Meadow Mari', 'mk': 'Macedonian', 'ml': 'Malayalam', 'mn': 'Mongolian', 'mni': 'Meetei Lon', 'mos': 'Mossi', 'mr': 'Marathi', 'mrj': 'Hill Mari', 'ms': 'Malay', 'mt': 'Maltese', 'my': 'Burmese', 'myv': 'Erzya', 'nan-tw': 'Taiwanese (Minnan)', 'nb-NO': 'Norwegian Bokmål', 'nd': 'IsiNdebele (North)', 'ne-NP': 'Nepali', 'nia': 'Nias', 'nl': 'Dutch', 'nn-NO': 'Norwegian Nynorsk', 'nr': 'IsiNdebele (South)', 'nso': 'Northern Sotho', 'nyn': 'Runyankole', 'oc': 'Occitan', 'om': 'Afaan Ormoo', 'or': 'Odia', 'pa-IN': 'Punjabi', 'pap-AW': 'Papiamento (Aruba)', 'pl': 'Polish', 'ps': 'Pashto', 'pt': 'Portuguese', 'quc': "K'iche'", 'quy': 'Quechua Chanka', 'rm-sursilv': 'Romansh Sursilvan', 'rm-vallader': 'Romansh Vallader', 'ro': 'Romanian', 'ru': 'Russian', 'rw': 'Kinyarwanda', 'sah': 'Sakha', 'sat': 'Santali (Ol Chiki)', 'sc': 'Sardinian', 'scn': 'Sicilian', 'sdh': 'Southern Kurdish', 'shi': 'Shilha', 'si': 'Sinhala', 'sk': 'Slovak', 'skr': 'Saraiki', 'sl': 'Slovenian', 'snk': 'Soninke', 'so': 'Somali', 'sq': 'Albanian', 'sr': 'Serbian', 'ss': 'Siswati', 'st': 'Southern Sotho', 'sv-SE': 'Swedish', 'sw': 'Swahili', 'syr': 'Syriac', 'ta': 'Tamil', 'te': 'Telugu', 'tg': 'Tajik', 'th': 'Thai', 'ti': 'Tigrinya', 'tig': 'Tigre', 'tk': 'Turkmen', 'tl': 'Tagalog', 'tn': 'Setswana', 'tok': 'Toki Pona', 'tr': 'Turkish', 'ts': 'Xitsonga', 'tt': 'Tatar', 'tw': 'Twi', 'ty': 'Tahitian', 'uby': 'Ubykh', 'udm': 'Udmurt', 'ug': 'Uyghur', 'uk': 'Ukrainian', 'ur': 'Urdu', 'uz': 'Uzbek', 've': 'Tshivenda', 'vec': 'Venetian', 'vi': 'Vietnamese', 'vot': 'Votic', 'xh': 'Xhosa', 'yi': 'Yiddish', 'yo': 'Yoruba', 'yue': 'Cantonese', 'zgh': 'Tamazight', 'zh-CN': 'Chinese (China)', 'zh-HK': 'Chinese (Hong Kong)', 'zh-TW': 'Chinese (Taiwan)', 'zu': 'Zulu'}
release_stats.py ADDED
@@ -0,0 +1 @@
 
 
1
+ STATS = {'bundleURLTemplate': 'cv-corpus-11.0-2022-09-21/cv-corpus-11.0-2022-09-21-{locale}.tar.gz', 'date': '2022-09-21', 'name': 'Common Voice Corpus 11.0', 'multilingual': True, 'locales': {'en': {'duration': 11152496587, 'buckets': {'dev': 16354, 'invalidated': 252599, 'other': 290846, 'reported': 4366, 'test': 16354, 'train': 948736, 'validated': 1618225}, 'reportedSentences': 4294, 'clips': 2161670, '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': 0.45, 'female': 0.15, 'other': 0.02}}, 'users': 84673, 'size': 79751937788, 'checksum': '0efd86ca6b40641b55d1411b7d3b1f1ab8626de4b207504953706df201d198a5', 'avgDurationSecs': 5.159, 'validDurationSecs': 8348752.95, 'totalHrs': 3097.91, 'validHrs': 2319.09}, 'fa': {'buckets': {'dev': 10288, 'invalidated': 13793, 'other': 24401, 'reported': 2168, 'test': 10288, 'train': 26951, 'validated': 309996}, 'reportedSentences': 2159, 'duration': 1392397316, 'clips': 348190, 'splits': {'accent': {'': 1}, 'age': {'': 0.25, 'twenties': 0.31, 'thirties': 0.37, 'fifties': 0.02, 'fourties': 0.03, 'teens': 0.03, 'sixties': 0}, 'gender': {'': 0.22, 'male': 0.71, 'female': 0.07, 'other': 0}}, 'users': 4124, 'size': 10237548588, 'checksum': 'e40247da130302d1dd71e5f25742a0f2f61e8627e7b674c13294967a23f6cf47', 'avgDurationSecs': 3.999, 'validDurationSecs': 1239661.1, 'totalHrs': 386.77, 'validHrs': 344.35}, 'fr': {'buckets': {'dev': 16089, 'invalidated': 57607, 'other': 14359, 'reported': 6586, 'test': 16089, 'train': 485034, 'validated': 652051}, 'reportedSentences': 6510, 'duration': 3623103766, 'clips': 724017, 'splits': {'accent': {'': 1}, 'age': {'twenties': 0.17, 'thirties': 0.16, '': 0.36, 'teens': 0.03, 'fourties': 0.14, 'fifties': 0.1, 'sixties': 0.03, 'seventies': 0.01, 'eighties': 0, 'nineties': 0}, 'gender': {'male': 0.61, '': 0.28, 'female': 0.1, 'other': 0.01}}, 'users': 16785, 'size': 25947906602, 'checksum': 'f763f9b1817280cd37db4d4161a9afc76257024d5bb54951a5987464e1e2ebb4', 'avgDurationSecs': 5.004, 'validDurationSecs': 3262973.706, 'totalHrs': 1006.41, 'validHrs': 906.38}, 'es': {'buckets': {'dev': 15520, 'invalidated': 52095, 'other': 1180383, 'reported': 2033, 'test': 15520, 'train': 230467, 'validated': 305875}, 'reportedSentences': 2019, 'duration': 7475216238, 'clips': 1538353, 'splits': {'accent': {'': 1}, 'age': {'thirties': 0.1, '': 0.13, 'fifties': 0.04, 'twenties': 0.56, 'teens': 0.08, 'fourties': 0.03, 'sixties': 0.06, 'eighties': 0, 'seventies': 0, 'nineties': 0}, 'gender': {'male': 0.54, '': 0.13, 'other': 0, 'female': 0.33}}, 'users': 24516, 'size': 47288212406, 'checksum': '319ae22d17dc2158322bb189a4938faba0debe653b611a325ee80c672be277a1', 'avgDurationSecs': 4.859, 'validDurationSecs': 1486318.008, 'totalHrs': 2076.44, 'validHrs': 412.86}, 'sl': {'buckets': {'dev': 1206, 'invalidated': 251, 'other': 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