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Task: ASR
Release Date: 6/17/2026
Format: MP3
Size: 242.71 MB
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A collection of read speech recordings in Basaa (Basaa).
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.
bas)This datasheet is for cv-corpus-26.0-2026-06-12 of the Mozilla Common Voice Scripted Speech dataset for Basaa [Basaa - bas]. The dataset contains 12496 clips representing 13.56 hours of recorded speech (12.09 hours validated) from 57 speakers, recorded from a text corpus of 5,331 sentences.
Basaa is a narrow Bantu language spoken across a geographical area spanning three administrative regions in Cameroon: the Centre, Littoral and South regions. It is estimated that there are currently around 600,000–700,000 speakers. This figure includes different varieties, as well as diasporic populations who identify as Basaa speakers.
The vitality of the Basaa language is stable (Ethnologue online). However, intergenerational transmission of Basaa is increasingly threatened among parents aged 50 and under, particularly in urban areas.
Although Basaa is taught in schools, this does not significantly impact the vitality of the language, mainly due to the current pedagogical approach, which relies on rule-based and descriptivist teaching methods.
The glossonym 'Basaa' is a generic term that encompasses a range of varieties, the speakers of which may identify with the 'Basaa' label to varying degrees, depending on a complex set of geographical, social, political, situational and pragmatic factors. Whether a language variant is considered Basaa depends greatly on the perspective of the person 'telling the story'. Some of the most commonly acknowledged varieties of Basaa include:
Mbene
Bikok
Babimbi
Basaa ba Omeng
Basaa ba Yabasi Basaa ba Duala
Ndog-Bikim
Other varieties, such as Ndonga, Mbaa (also known as Mbay-Bati) and Hijuk, may also be classified as Basaa. However, as previously mentioned, not everyone agrees on this classification.
| Code | Accent | Clips | Speakers |
|---|---|---|---|
| - | 5 (0.0%) | 1 (1.8%) |
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 | 15 (0.1%) | 1 (1.8%) |
| female_feminine | Female, feminine | 55 (0.4%) | 5 (8.8%) |
| transgender | Transgender | - | - |
| non-binary | Non-binary | - | - |
| do_not_wish_to_say | Prefer not to say | - | - |
| - | Unspecified | 12,426 (99.4%) | 52 (91.2%) |
Gender declared: 70 of 12,496 clips (0.6%), 5 of 57 speakers (8.8%)
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 | 15 (0.1%) | 1 (1.8%) |
| twenties | Twenties | 20 (0.2%) | 2 (3.5%) |
| thirties | Thirties | 15 (0.1%) | 2 (3.5%) |
| fourties | Fourties | 7,621 (61.0%) | 3 (5.3%) |
| fifties | Fifties | - | - |
| sixties | Sixties | - | - |
| seventies | Seventies | - | - |
| eighties | Eighties | - | - |
| nineties | Nineties | - | - |
| - | Unspecified | 4,825 (38.6%) | 52 (91.2%) |
Age declared: 7,671 of 12,496 clips (61.4%), 5 of 57 speakers (8.8%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 11,139 (89.1%) |
| Invalidated | 1,214 (9.7%) |
| Other | 143 (1.1%) |
Training splits
| Split | Clips |
|---|---|
| Train | 2,112 (19.0%) |
| Dev | 1,324 (11.9%) |
| Test | 1,551 (13.9%) |
Training split coverage: 4,987 of 11,139 validated clips (44.8%)
The dataset contains 11139 validated, 1214 invalidated, and 143 unresolved clips. The average clip duration is 3.909 seconds.
Validated sentences: 5,226
| Category | Count |
|---|---|
| Unvalidated sentences | 105 |
| Pending sentences | 94 |
| Rejected sentences | 11 |
| Reported sentences | 8 |
The corpus contains 5,331 sentences: 5,226 validated and 105 unvalidated (94 pending review, 11 rejected), with 8 reported for review.
Basaa has several competing writing norms. The most widely used are the Catholic missionary orthography, the Prostestant missionary orthography, and a version of the General Alphabet of Cameroonian Languages that was adapted to Basaa.
This dataset is mostly based on the Protestant missionary's orthography, with minor alterations concerning, for example, the signaling of b as implosive [ɓ]. For example, m'bôñ "cassava" vs mbôñ "poison". Other alterations includes the signaling of the n- prefix followed by the y symbol, to distinguish it from the complex symbol ny. For example, nyo "mouth" vs a n'yo "he stole palm wine from the palm trunk".
There follows a randomly selected sample of five sentences from the corpus.
Libok li mbep.
U nnyémlaha ki bo?
ñkôô woñ u nhudla.
Malép ma ntôyôy i tun yem.
Me ñkena bakén i njel.
| Source | Sentences |
|---|---|
| sentence-collector | 5,015 (96.0%) |
| From Prof. Njock's dictionary, permission gained by Dr. Emmanuel Ngue Um | 166 (3.2%) |
| Other | 45 (0.9%) |
| Code | Domain | Clips | Speakers |
|---|---|---|---|
| general | General | 8 (0.1%) | 4 (7.0%) |
| agriculture_food | Agriculture and Food | - | - |
| automotive_transport | Automotive and Transport | - | - |
| finance | Finance | - | - |
| service_retail | Service and Retail | - | - |
| healthcare | Healthcare | - | - |
| history_law_government | History, Law and Government | - | - |
| media_entertainment | Media and Entertainment | - | - |
| nature_environment | Nature and Environment | - | - |
| news_current_affairs | News and Current Affairs | - | - |
| technology_robotics | Technology and Robotics | - | - |
| language_fundamentals | Language Fundamentals | - | - |
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)
Emmanuel Ngué Um
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