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Task: ASR
Release Date: 3/25/2026
Format: MP3
Size: 28.39 GB
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A collection of read speech recordings in French (Français).
Restrictions/Special Constraints
None provided.
Forbidden Usage
It is forbidden to attempt to determine the identity of speakers in the Common Voice datasets. It is forbidden to re-host or re-share this dataset.
Intended Use
This dataset is intended to be used for training and evaluating automatic speech recognition (ASR) models. It may also be used for applications relating to computer-aided language learning (CALL) and language or heritage revitalisation.
fr)This datasheet is for cv-corpus-25.0-2026-03-09 of the Mozilla Common Voice Scripted Speech dataset for French [Français - fr]. The dataset contains 864728 clips representing 1209.71 hours of recorded speech (1095.87 hours validated) from 21003 speakers, recorded from a text corpus of 1,692,862 sentences.
French is a Romance language. It is the official language of 26 countries and is spoken across around 50 countries.
| Code | Variant | Clips | Speakers |
|---|---|---|---|
| fr-metro | Français de métropole | 542,845 (62.8%) | 4,639 (22.1%) |
| fr-europe | Français d'Europe | 26,543 (3.1%) | 442 (2.1%) |
| fr-namerica | Français d'Amérique du Nord | 14,424 (1.7%) | 309 (1.5%) |
| fr-safrica | Français d'Afrique subsaharienne et des îles africaines | 2,066 (0.2%) | 87 (0.4%) |
| fr-droum | Français des départements et régions d'outre-mer | 1,936 (0.2%) | 40 (0.2%) |
| fr-nafrica | Français du nord de l'Afrique | 1,342 (0.2%) | 61 (0.3%) |
| fr-samerica | Français d'Amérique du Sud et des Caraïbes | 90 (0.0%) | 6 (0.0%) |
| Code | Accent | Clips | Speakers |
|---|---|---|---|
| canada | Français du Canada | 12,869 (1.5%) | 275 (1.3%) |
| belgium | Français de Belgique | 11,381 (1.3%) | 226 (1.1%) |
| switzerland | Français de Suisse | 5,916 (0.7%) | 141 (0.7%) |
| united_states | Français des États-Unis | 1,610 (0.2%) | 41 (0.2%) |
| reunion | Français de La Réunion | 1,307 (0.2%) | 16 (0.1%) |
| benin | Français du Bénin | 1,073 (0.1%) | 7 (0.0%) |
| algeria | Français d’Algérie | 1,070 (0.1%) | 26 (0.1%) |
| germany | Français d’Allemagne | 552 (0.1%) | 26 (0.1%) |
| fr-metro-north | Français du nord de la France | 535 (0.1%) | 2 (0.0%) |
| united_kingdom | Français du Royaume-Uni | 502 (0.1%) | 25 (0.1%) |
| haiti | Français d’Haïti | 498 (0.1%) | 7 (0.0%) |
| madagascar | Français de Madagascar | 283 (0.0%) | 12 (0.1%) |
| fr-metro-south | Français du sud de la France | 229 (0.0%) | 9 (0.0%) |
| morocco | Français du Maroc | 211 (0.0%) | 30 (0.1%) |
| fr-metro-east | Français de l'est de la France | 209 (0.0%) | 3 (0.0%) |
| cote_d_ivoire | Français de Côte d’Ivoire | 201 (0.0%) | 18 (0.1%) |
| senegal | Français du Sénégal | 197 (0.0%) | 16 (0.1%) |
| french_guiana | Français de Guyane | 188 (0.0%) | 3 (0.0%) |
| guadeloupe | Français de Guadeloupe | 175 (0.0%) | 13 (0.1%) |
| italy | Français d’Italie | 171 (0.0%) | 9 (0.0%) |
| fr-metro-west | Français de l'ouest de la France | 166 (0.0%) | 7 (0.0%) |
| cameroon | Français du Cameroun | 163 (0.0%) | 16 (0.1%) |
| new_caledonia | Français de Nouvelle-Calédonie | 159 (0.0%) | 3 (0.0%) |
| romania | Français de Roumanie | 150 (0.0%) | 6 (0.0%) |
| tunisia | Français de Tunisie | 121 (0.0%) | 16 (0.1%) |
| monaco | Français de Monaco | 111 (0.0%) | 3 (0.0%) |
| netherlands | Français des Pays-Bas | 101 (0.0%) | 4 (0.0%) |
| martinique | Français de Martinique | 100 (0.0%) | 7 (0.0%) |
| congo_kinshasa | Français du Congo (Kinshasa) | 45 (0.0%) | 5 (0.0%) |
| mali | Français du Mali | 39 (0.0%) | 4 (0.0%) |
| luxembourg | Français du Luxembourg | 20 (0.0%) | 3 (0.0%) |
| st_pierre_et_miquelon | Français de Saint-Pierre-et-Miquelon | 15 (0.0%) | 1 (0.0%) |
| mayotte | Français de Mayotte | 12 (0.0%) | 1 (0.0%) |
| mauritius | Français de l’Île Maurice | 10 (0.0%) | 2 (0.0%) |
| - | Other | 7,511 (0.9%) | 244 (1.2%) |
The dataset includes the following self-declared age and gender distributions. A coverage summary is shown below each table.
Self-declared gender information. The table shows clip and speaker counts with percentages. Speakers who did not declare a gender are listed as Unspecified. A dash (-) indicates zero.
| Code | Gender | Clips | Speakers |
|---|---|---|---|
| male_masculine | Male, masculine | 491,443 (56.8%) | 3,878 (18.5%) |
| female_feminine | Female, feminine | 92,369 (10.7%) | 1,010 (4.8%) |
| transgender | Transgender | 5 (0.0%) | 1 (0.0%) |
| non-binary | Non-binary | 249 (0.0%) | 3 (0.0%) |
| do_not_wish_to_say | Prefer not to say | 302 (0.0%) | 4 (0.0%) |
| - | Unspecified | 280,360 (32.4%) | 16,786 (79.9%) |
Gender declared: 584,368 of 864,728 clips (67.6%), 4,217 of 21,003 speakers (20.1%)
Self-declared age information. The table shows clip and speaker counts with percentages. Speakers who did not declare an age are listed as Unspecified. A dash (-) indicates zero.
| Code | Age | Clips | Speakers |
|---|---|---|---|
| teens | Teens | 24,515 (2.8%) | 444 (2.1%) |
| twenties | Twenties | 147,928 (17.1%) | 1,732 (8.2%) |
| thirties | Thirties | 125,467 (14.5%) | 1,156 (5.5%) |
| fourties | Fourties | 122,937 (14.2%) | 855 (4.1%) |
| fifties | Fifties | 81,444 (9.4%) | 496 (2.4%) |
| sixties | Sixties | 28,974 (3.4%) | 326 (1.6%) |
| seventies | Seventies | 9,224 (1.1%) | 121 (0.6%) |
| eighties | Eighties | 212 (0.0%) | 7 (0.0%) |
| nineties | Nineties | 5 (0.0%) | 1 (0.0%) |
| - | Unspecified | 324,022 (37.5%) | 16,619 (79.1%) |
Age declared: 540,706 of 864,728 clips (62.5%), 4,384 of 21,003 speakers (20.9%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 783,357 (90.6%) |
| Invalidated | 68,142 (7.9%) |
| Other | 13,229 (1.5%) |
Training splits
| Split | Clips |
|---|---|
| Train | 613,431 (78.3%) |
| Dev | 16,201 (2.1%) |
| Test | 16,201 (2.1%) |
Training split coverage: 645,833 of 783,357 validated clips (82.4%)
The dataset contains 783357 validated, 68142 invalidated, and 13229 unresolved clips. The average clip duration is 5.036 seconds.
Validated sentences: 1,649,097
| Category | Count |
|---|---|
| Unvalidated sentences | 43,765 |
| Pending sentences | 43,638 |
| Rejected sentences | 127 |
| Reported sentences | 7,562 |
The corpus contains 1,692,862 sentences: 1,649,097 validated and 43,765 unvalidated (43,638 pending review, 127 rejected), with 7,562 reported for review.
The French language uses the 26 letters of the Latin alphabet with the addition of two ligatures (æ, œ) and five diacritics.
a à â æ b c ç d e é è ê ë f g h i î ï j k l m n ô œ p q r s t u ù û ü v w x y ÿ z
There follows a randomly selected sample of five sentences from the corpus.
Le canton de Tende était composé des communes de Tende et La Brigue.
Cette décision fait grand bruit.
Un paludier est un travailleur qui récolte le sel des marais salants.
Les jardins sont ouverts au public.
Église mononef, elle ne présente aucun caractère particulier.
| Source | Sentences |
|---|---|
| wiki-2 | 719,731 (43.8%) |
| wiki-1 | 717,145 (43.7%) |
| sentence-collector | 103,289 (6.3%) |
| issue2259_deleted_export_readd_fixed | 62,385 (3.8%) |
| Other | 39,075 (2.4%) |
| Code | Domain | Clips | Speakers |
|---|---|---|---|
| general | General | 70 (0.0%) | 53 (0.3%) |
| agriculture_food | Agriculture and Food | - | - |
| automotive_transport | Automotive and Transport | 1 (0.0%) | 1 (0.0%) |
| finance | Finance | 1 (0.0%) | 1 (0.0%) |
| service_retail | Service and Retail | - | - |
| healthcare | Healthcare | 5 (0.0%) | 4 (0.0%) |
| history_law_government | History, Law and Government | 19 (0.0%) | 17 (0.1%) |
| media_entertainment | Media and Entertainment | 17 (0.0%) | 13 (0.1%) |
| nature_environment | Nature and Environment | 8 (0.0%) | 8 (0.0%) |
| news_current_affairs | News and Current Affairs | 2 (0.0%) | 2 (0.0%) |
| technology_robotics | Technology and Robotics | 18 (0.0%) | 12 (0.1%) |
| language_fundamentals | Language Fundamentals | 7 (0.0%) | 5 (0.0%) |
Each row of a tsv file represents a single audio clip, and contains the following information:
client_id - hashed UUID of a given user
path - relative path of the audio file
text - supposed transcription of the audio
up_votes - number of people who said audio matches the text
down_votes - number of people who said audio does not match text
age - age of the speaker1
gender - gender of the speaker1
accents - accents of the speaker1
variant - variant of the language1
segment - if sentence belongs to a custom dataset segment, it will be listed here
prompt_upvotes - number of upvotes the sentence prompt received
prompt_reports - number of reports the sentence prompt received
is_edited - whether the clip's transcription has been edited
validated_sentences.tsvThe validated_sentences.tsv file contains one row per validated sentence in the text corpus:
sentence_id - unique identifier for the sentence
sentence - the sentence text
variant - the variant of the language
sentence_domain - the domain(s) the sentence belongs to
source - the source the sentence was collected from
is_used - whether the sentence is still in circulation for recording
clips_count - number of clips recorded for this sentence
unvalidated_sentences.tsvThe unvalidated_sentences.tsv file contains one row per unvalidated sentence in the text corpus:
sentence_id - unique identifier for the sentence
sentence - the sentence text
variant - the variant of the language
sentence_domain - the domain(s) the sentence belongs to
source - the source the sentence was collected from
up_votes - number of upvotes the sentence received
down_votes - number of downvotes the sentence received
status - current status of the sentence (pending or rejected)
This dataset is released under the Creative Commons Zero (CC-0) licence. By downloading this data you agree to not determine the identity of speakers in the dataset.
For a full list of age, gender, and accent options, see the demographics spec. These will only be reported if the speaker opted in to provide that information. ↩ ↩2 ↩3 ↩4