Datasets:
common_voice

	---
	pretty_name: Common Voice
	annotations_creators:
	- crowdsourced
	language_creators:
	- crowdsourced
	languages:
	- ab
	- ar
	- as
	- br
	- ca
	- cnh
	- cs
	- cv
	- cy
	- de
	- dv
	- el
	- en
	- eo
	- es
	- et
	- eu
	- fa
	- fi
	- fr
	- fy-NL
	- ga-IE
	- hi
	- hsb
	- hu
	- ia
	- id
	- it
	- ja
	- ka
	- kab
	- ky
	- lg
	- lt
	- lv
	- mn
	- mt
	- nl
	- or
	- pa-IN
	- pl
	- pt
	- rm-sursilv
	- rm-vallader
	- ro
	- ru
	- rw
	- sah
	- sl
	- sv-SE
	- ta
	- th
	- tr
	- tt
	- uk
	- vi
	- vot
	- zh-CN
	- zh-HK
	- zh-TW
	licenses:
	- cc0-1-0
	multilinguality:
	- multilingual
	size_categories:
	ab:
	- n<1K
	ar:
	- 10K<n<100K
	as:
	- n<1K
	br:
	- 10K<n<100K
	ca:
	- 100K<n<1M
	cnh:
	- 1K<n<10K
	cs:
	- 10K<n<100K
	cv:
	- 10K<n<100K
	cy:
	- 10K<n<100K
	de:
	- 100K<n<1M
	dv:
	- 1K<n<10K
	el:
	- 10K<n<100K
	en:
	- 100K<n<1M
	eo:
	- 10K<n<100K
	es:
	- 100K<n<1M
	et:
	- 10K<n<100K
	eu:
	- 10K<n<100K
	fa:
	- 10K<n<100K
	fi:
	- 1K<n<10K
	fr:
	- 100K<n<1M
	fy-NL:
	- 10K<n<100K
	ga-IE:
	- 1K<n<10K
	hi:
	- n<1K
	hsb:
	- 1K<n<10K
	hu:
	- 1K<n<10K
	ia:
	- 1K<n<10K
	id:
	- 10K<n<100K
	it:
	- 100K<n<1M
	ja:
	- 1K<n<10K
	ka:
	- 1K<n<10K
	kab:
	- 100K<n<1M
	ky:
	- 10K<n<100K
	lg:
	- 1K<n<10K
	lt:
	- 1K<n<10K
	lv:
	- 1K<n<10K
	mn:
	- 1K<n<10K
	mt:
	- 10K<n<100K
	nl:
	- 10K<n<100K
	or:
	- 1K<n<10K
	pa-IN:
	- 1K<n<10K
	pl:
	- 10K<n<100K
	pt:
	- 10K<n<100K
	rm-sursilv:
	- 1K<n<10K
	rm-vallader:
	- 1K<n<10K
	ro:
	- 1K<n<10K
	ru:
	- 10K<n<100K
	rw:
	- 100K<n<1M
	sah:
	- 1K<n<10K
	sl:
	- 1K<n<10K
	sv-SE:
	- 1K<n<10K
	ta:
	- 10K<n<100K
	th:
	- 10K<n<100K
	tr:
	- 1K<n<10K
	tt:
	- 10K<n<100K
	uk:
	- 10K<n<100K
	vi:
	- 1K<n<10K
	vot:
	- n<1K
	zh-CN:
	- 10K<n<100K
	zh-HK:
	- 10K<n<100K
	zh-TW:
	- 10K<n<100K
	source_datasets:
	- extended\|common_voice
	task_categories:
	- speech-processing
	task_ids:
	- automatic-speech-recognition
	paperswithcode_id: common-voice
	---

	# Dataset Card for common_voice

	## Table of Contents
	- [Dataset Description](#dataset-description)
	- [Dataset Summary](#dataset-summary)
	- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
	- [Languages](#languages)
	- [Dataset Structure](#dataset-structure)
	- [Data Instances](#data-instances)
	- [Data Fields](#data-fields)
	- [Data Splits](#data-splits)
	- [Dataset Creation](#dataset-creation)
	- [Curation Rationale](#curation-rationale)
	- [Source Data](#source-data)
	- [Annotations](#annotations)
	- [Personal and Sensitive Information](#personal-and-sensitive-information)
	- [Considerations for Using the Data](#considerations-for-using-the-data)
	- [Social Impact of Dataset](#social-impact-of-dataset)
	- [Discussion of Biases](#discussion-of-biases)
	- [Other Known Limitations](#other-known-limitations)
	- [Additional Information](#additional-information)
	- [Dataset Curators](#dataset-curators)
	- [Licensing Information](#licensing-information)
	- [Citation Information](#citation-information)
	- [Contributions](#contributions)

	## Dataset Description

	- Homepage: https://commonvoice.mozilla.org/en/datasets
	- Repository: https://github.com/common-voice/common-voice
	- Paper: https://commonvoice.mozilla.org/en/datasets
	- Leaderboard: [Needs More Information]
	- Point of Contact: [Needs More Information]

	### Dataset Summary

	The Common Voice dataset consists of a unique MP3 and corresponding text file. Many of the 9,283 recorded hours in the dataset also include demographic metadata like age, sex, and accent that can help train the accuracy of speech recognition engines.

	The dataset currently consists of 7,335 validated hours in 60 languages, but were always adding more voices and languages. Take a look at our Languages page to request a language or start contributing.

	### Supported Tasks and Leaderboards

	[Needs More Information]

	### Languages

	English

	## Dataset Structure

	### Data Instances

	A typical data point comprises the path to the audio file, called path and its sentence. Additional fields include accent, age, client_id, up_votes down_votes, gender, locale and segment.

	`
	{'accent': 'netherlands', 'age': 'fourties', 'client_id': 'bbbcb732e0f422150c30ff3654bbab572e2a617da107bca22ff8b89ab2e4f124d03b6a92c48322862f60bd0179ae07baf0f9b4f9c4e11d581e0cec70f703ba54', 'down_votes': 0, 'gender': 'male', 'locale': 'nl', 'path': 'nl/clips/common_voice_nl_23522441.mp3', 'segment': "''", 'sentence': 'Ik vind dat een dubieuze procedure.', 'up_votes': 2, 'audio': {'path': `nl/clips/common_voice_nl_23522441.mp3', 'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, 0.00091553, 0.00085449], dtype=float32), 'sampling_rate': 48000}
	`

	### Data Fields

	client_id: An id for which client (voice) made the recording

	path: The path to the audio file

	audio: 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]`.

	sentence: The sentence the user was prompted to speak

	up_votes: How many upvotes the audio file has received from reviewers

	down_votes: How many downvotes the audio file has received from reviewers

	age: The age of the speaker.

	gender: The gender of the speaker

	accent: Accent of the speaker

	locale: The locale of the speaker

	segment: Usually empty field

	### Data Splits

	The speech material has been subdivided into portions for dev, train, test, validated, invalidated, reported and other.

	The validated data is data that has been validated with reviewers and recieved upvotes that the data is of high quality.

	The invalidated data is data has been invalidated by reviewers
	and recieved downvotes that the data is of low quality.

	The reported data is data that has been reported, for different reasons.

	The other data is data that has not yet been reviewed.

	The dev, test, train are all data that has been reviewed, deemed of high quality and split into dev, test and train.

	## Dataset Creation

	### Curation Rationale

	[Needs More Information]

	### Source Data

	#### Initial Data Collection and Normalization

	[Needs More Information]

	#### Who are the source language producers?

	[Needs More Information]

	### Annotations

	#### Annotation process

	[Needs More Information]

	#### Who are the annotators?

	[Needs More Information]

	### Personal and Sensitive Information

	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.

	## Considerations for Using the Data

	### Social Impact of Dataset

	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.

	### Discussion of Biases

	[More Information Needed]

	### Other Known Limitations

	[More Information Needed]

	## Additional Information

	### Dataset Curators

	[More Information Needed]

	### Licensing Information

	Public Domain, [CC-0](https://creativecommons.org/share-your-work/public-domain/cc0/)

	### Citation Information

	```
	@inproceedings{commonvoice:2020,
	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.},
	title = {Common Voice: A Massively-Multilingual Speech Corpus},
	booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)},
	pages = {4211--4215},
	year = 2020
	}
	```

	### Contributions

	Thanks to [@BirgerMoell](https://github.com/BirgerMoell) for adding this dataset.