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Release Date: 9/17/2026
Format: MP3
Size: 28.55 GB
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-27.0-2026-09-11 of the Mozilla Common Voice Scripted Speech dataset for French [Français - fr]. The dataset contains 869961 clips representing 1217.36 hours of recorded speech (1108.28 hours validated) from 21116 speakers, recorded from a text corpus of 1,817,452 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 | 546,435 (62.8%) | 4,657 (22.1%) |
| fr-europe | Français d'Europe | 27,240 (3.1%) | 454 (2.2%) |
| fr-namerica | Français d'Amérique du Nord | 14,424 (1.7%) | 309 (1.5%) |
| fr-safrica | Français d'Afrique subsaharienne et des îles africaines | 2,086 (0.2%) | 91 (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 | 1,454 (0.2%) | 62 (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 | 6,169 (0.7%) | 143 (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%) |
| fr-metro-north | Français du nord de la France | 720 (0.1%) | 6 (0.0%) |
| germany | Français d’Allemagne | 552 (0.1%) | 26 (0.1%) |
| united_kingdom | Français du Royaume-Uni | 502 (0.1%) | 25 (0.1%) |
| haiti | Français d’Haïti | 498 (0.1%) | 7 (0.0%) |
| fr-metro-west | Français de l'ouest de la France | 361 (0.0%) | 13 (0.1%) |
| fr-metro-south | Français du sud de la France | 319 (0.0%) | 12 (0.1%) |
| madagascar | Français de Madagascar | 283 (0.0%) | 12 (0.1%) |
| fr-metro-east | Français de l'est de la France | 249 (0.0%) | 8 (0.0%) |
| morocco | Français du Maroc | 216 (0.0%) | 31 (0.1%) |
| cote_d_ivoire | Français de Côte d’Ivoire | 211 (0.0%) | 20 (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%) |
| 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) | 48 (0.0%) | 6 (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%) |
| comoros | Français des Comores | 5 (0.0%) | 1 (0.0%) |
| togo | Français de la République du Togo | 5 (0.0%) | 1 (0.0%) |
| - | Other | 7,521 (0.9%) | 246 (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 | 494,623 (56.9%) | 3,878 (18.4%) |
| female_feminine | Female, feminine | 92,814 (10.7%) | 1,015 (4.8%) |
| transgender | Transgender | 5 (0.0%) | 1 (0.0%) |
| non-binary | Non-binary | 264 (0.0%) | 3 (0.0%) |
| do_not_wish_to_say | Prefer not to say | 302 (0.0%) | 4 (0.0%) |
| - | Unspecified | 281,953 (32.4%) | 16,896 (80.0%) |
Gender declared: 588,008 of 869,961 clips (67.6%), 4,220 of 21,116 speakers (20.0%)
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 | 24,625 (2.8%) | 446 (2.1%) |
| twenties | Twenties | 147,960 (17.0%) | 1,734 (8.2%) |
| thirties | Thirties | 125,487 (14.4%) | 1,156 (5.5%) |
| fourties | Fourties | 123,974 (14.3%) | 858 (4.1%) |
| fifties | Fifties | 83,934 (9.6%) | 498 (2.4%) |
| sixties | Sixties | 29,147 (3.4%) | 329 (1.6%) |
| seventies | Seventies | 9,375 (1.1%) | 121 (0.6%) |
| eighties | Eighties | 212 (0.0%) | 7 (0.0%) |
| nineties | Nineties | 5 (0.0%) | 1 (0.0%) |
| - | Unspecified | 325,242 (37.4%) | 16,725 (79.2%) |
Age declared: 544,719 of 869,961 clips (62.6%), 4,391 of 21,116 speakers (20.8%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 792,011 (91.0%) |
| Invalidated | 68,684 (7.9%) |
| Other | 9,266 (1.1%) |
Training splits
| Split | Clips |
|---|---|
| Train | 621,982 (78.5%) |
| Dev | 16,207 (2.0%) |
| Test | 16,207 (2.0%) |
Training split coverage: 654,396 of 792,011 validated clips (82.6%)
The dataset contains 792011 validated, 68684 invalidated, and 9266 unresolved clips. The average clip duration is 5.038 seconds.
Validated sentences: 1,661,012
| Category | Count |
|---|---|
| Unvalidated sentences | 156,440 |
| Pending sentences | 156,282 |
| Rejected sentences | 158 |
| Reported sentences | 7,592 |
The corpus contains 1,817,452 sentences: 1,661,012 validated and 156,440 unvalidated (156,282 pending review, 158 rejected), with 7,592 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.
La dernière partie du livre contient une série de prières.
Le mois suivant, Christine Woods obtient le rôle de la femme décédée de Ryan.
Et Démonax de Chypre, Epicharme de Cos
Les fils de Noé engendrent les diverses nations du globe.
Il est également décoré comme commandeur des Arts et des Lettres.
| Source | Sentences |
|---|---|
| wiki-2 | 719,731 (43.5%) |
| wiki-1 | 717,145 (43.4%) |
| sentence-collector | 103,289 (6.2%) |
| issue2259_deleted_export_readd_fixed | 62,385 (3.8%) |
| Other | 50,990 (3.1%) |
| Code | Domain | Clips | Speakers |
|---|---|---|---|
| general | General | 219 (0.0%) | 72 (0.3%) |
| agriculture_food | Agriculture and Food | 44 (0.0%) | 7 (0.0%) |
| automotive_transport | Automotive and Transport | 1 (0.0%) | 1 (0.0%) |
| finance | Finance | 1 (0.0%) | 1 (0.0%) |
| service_retail | Service and Retail | 48 (0.0%) | 8 (0.0%) |
| healthcare | Healthcare | 6 (0.0%) | 5 (0.0%) |
| history_law_government | History, Law and Government | 251 (0.0%) | 39 (0.2%) |
| media_entertainment | Media and Entertainment | 51 (0.0%) | 16 (0.1%) |
| nature_environment | Nature and Environment | 341 (0.0%) | 34 (0.2%) |
| news_current_affairs | News and Current Affairs | 2 (0.0%) | 2 (0.0%) |
| technology_robotics | Technology and Robotics | 43 (0.0%) | 16 (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
sentence - the sentence to be read aloud
sentence_id - unique identifier for the sentence
sentence_domain - domain classification(s) of the sentence
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
locale - locale code of the language
segment - if sentence belongs to a custom dataset segment, it will be listed here
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