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Task: ASR
Release Date: 6/17/2026
Format: MP3
Size: 109.74 MB
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A collection of spontaneous responses to questions 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 sps-corpus-4.0-2026-06-12 of the Mozilla Common Voice Spontaneous Speech dataset for Basaa [Basaa - bas]. The dataset contains 773 clips representing 5.37 hours of recorded speech (5.06 hours validated) from 11 speakers.
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.
The dataset clips are categorised by transcription status and training-set assignment. The following tables summarise the distribution.
| Bucket | Clips | % |
|---|---|---|
| Transcribed & Validated | 734 | 95.0% |
| Transcribed & Pending | 38 | 4.9% |
| Not transcribed | 1 | 0.1% |
| Bucket | Clips | % |
|---|---|---|
| Train | 276 | 35.7% |
| Dev | 252 | 32.6% |
| Test | 206 | 26.6% |
| Unassigned | 39 | 5.0% |
Training split coverage: 734 of 734 transcribed & validated clips (100.0%)
| Bucket | Clips | % |
|---|---|---|
| Validated | 734 | 95.1% |
| Pending | 38 | 4.9% |
| Edited | 500 | 64.8% |
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 questions used in the corpus.
Ba ntjo laa ntjobo ?
Ba mbéna kal le, "kon u kon we ndék maange, wa mal bé" ; hala a nkobla laa ?
I nkéla le, mut a nlama je bitatam to bikay, hi ndéé, he ndigi nuga bé. Inyu kii i nkéla hala ?
Inyu kii ba nsébél Um Nyobe le Mpôdôl ?
Nseñ u likil mulôm a nti bakil bé indéé a nsômbôl bii muda, u yé le kii ?
There follows a randomly selected sample of transcribed responses from the corpus.
I tehe yem, inyu boñ le matén ma Kamerun momasôna ma niñ ikédé nsañ, ya sômbla le matén ma Kamerun mamasôna ma n'neebana ndugi le ba yé jom jam jada. Ya sômbla le hile litén li bana tik i jam i i nla hôla inyu boñ le bôt ba salak ba kôsnaga minkus. Ya sômbla le bôt bobasôna ba kôgôl ngok yada. Ba gwéhék loñ yap inyu boñ le jam li lôl bañ i mbégdé inyu lo i tembee bon bap. Ha, matén ma nla niñ ikédé nsañ.
Itehe yem, ilibak lini le basañ ba bon ba nti bigond gwap môy le eeh Ngo a ba bé mu, li yé le, bana basañ ba nsômbôl le Mbog i kwo'o ; inyu le ijôy lini le Ngo, jon li ñunda le maange muda a nlôl toy i litén li Basaa.
Inyu ilamb nsugi, u nke i bikay, u yéñ bitôñ, u lo'o u jôa gwo, u téé gwo i juu. Ingeñ u n'nôgda me bi m'bel, u telel gwo. U yéñ ntjobo ni ntidil. U tét bitôñ. Ingeñ u m'mal tét bitôñ le u gwéé nyaa-bitôñ, u yéñ malép, u hôô nsugi. U téé wo i juu. Mu i nsugi u, u nla ha to nkôt u kôy-hisi, to nkôt u nyik, to umbe ntén u nlamb mu i kédé. Hala nyen ba nlamb nsugi. U kônde hilôba, hiomi, ni bas.
Minsômbi mi yé minténmintén ngandak. Hala a yé maliga. Me me ñañle béé nsômbi u kôy-hisi. Iba le mut a gwéé ngwo yéé i nsômbôl, a nkena yo i bikay, a ma bada masis méé ni bikakañ. Iba le a ñada ñwii u kôy-hisi le ngwo yéé i m'bok kôy-hisi, a m'bôdôl tém wo. Ingeñ a m'bol i homa ba nsébél le malogol, ñwemel u kôy-hisi, iba le a nhéya imalogol ma, kôy-hisi i mpam i ñwii, ngwo i gwel yo. To le iba le i n'nay le i mpam bé, a ha hyéé, a pep yo. I nla wél mu i ñwii. A a tém yo, a bada, to le i pam, ngwo i gwel.
Mulôm a nlama tehe bakil béé. A télép, a éba su. A ti pôs. A ti bijek bi loñ. A hôl muda. A bii nye. Imam ma mon mulôm a m'boñ ingéda i mpam le a bii muda i ipañ basañ béé.
Each row of a tsv file represents a single audio clip, and contains the following information:
client_id - hashed UUID of a given user
audio_id - numeric id for audio file
audio_file - audio file name
duration_ms - duration of audio in milliseconds
prompt_id - numeric id for prompt
prompt - question for user
transcription - transcription of the audio response
votes - number of people that who approved a given transcript
age - age of the speaker1
gender - gender of the speaker1
language - language name
split - for data modelling, which subset of the data does this clip pertain to
char_per_sec - how many characters of transcription per second of audio
quality_tags - some automated assessment of the transcription--audio pair, separated by |
transcription-length - character per second under 3 characters per second
speech-rate - characters per second over 30 characters per second
short-audio - audio length under 2 seconds
long-audio - audio length over 5 minutes
non-allowed-script - transcription contains characters from a writing system not associated with the language
mixed-script-words - a single word contains characters from multiple writing systems
mixed-script-transcription - transcription spans multiple writing systems, but each word consistently uses only one
Emmanuel Ngue Um <ngueum@gmail.com>
The compilation of this dataset was made possible thanks to grant awarded by the Mozilla Foundation
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