Datasets:
Tasks:
Automatic Speech Recognition
Multilinguality:
multilingual
Language Creators:
crowdsourced
Annotations Creators:
crowdsourced
Source Datasets:
extended|common_voice
License:
metadata
pretty_name: Common Voice
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- ab
- ar
- as
- br
- ca
- cnh
- cs
- cv
- cy
- de
- dv
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- hi
- hsb
- hu
- ia
- id
- it
- ja
- ka
- kab
- ky
- lg
- lt
- lv
- mn
- mt
- nl
- or
- pa
- pl
- pt
- rm
- ro
- ru
- rw
- sah
- sl
- sv
- ta
- th
- tr
- tt
- uk
- vi
- vot
- zh
language_bcp47:
- fy-NL
- ga-IE
- pa-IN
- rm-sursilv
- rm-vallader
- sv-SE
- zh-CN
- zh-HK
- zh-TW
license:
- cc0-1.0
multilinguality:
- multilingual
size_categories:
- 100K<n<1M
- 10K<n<100K
- 1K<n<10K
- n<1K
source_datasets:
- extended|common_voice
task_categories:
- automatic-speech-recognition
task_ids: []
paperswithcode_id: common-voice
configs:
- 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
dataset_info:
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Dataset Card for common_voice
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
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
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 for adding this dataset.