Common Voice Scripted Speech 25.0 - Basaa

Basaa — Basaa (bas)

This datasheet is for cv-corpus-25.0-2026-03-09 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.

Language

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.

Accents

Demographic information

The dataset includes the following self-declared age and gender distributions. A coverage summary is shown below each table.

Gender

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.

Gender declared: 70 of 12,496 clips (0.6%), 5 of 57 speakers (8.8%)

Age

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.

Age declared: 7,671 of 12,496 clips (61.4%), 5 of 57 speakers (8.8%)

Data splits for modelling

Clip buckets

Training splits

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.

Text corpus

Validated sentences: 5,226

The corpus contains 5,331 sentences: 5,226 validated and 105 unvalidated (94 pending review, 11 rejected), with 8 reported for review.

Writing system

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".

Sample

There follows a randomly selected sample of five sentences from the corpus.

1. Kôgaha mut yom i nyo.

2. Nsugut woñ u nnyôhna loñge munu lipondo.

3. Kii u ntuñglene lép?

4. Hohle nye jomb li dinyet.

5. U yé mut pénda.

Sources

Text domains

Fields

Clips

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.tsv

The 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.tsv

The 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)

Get involved

Community links

• Common Voice translators on Pontoon

• Common Voice Communities

Discussions

• Common Voice on Matrix

• Common Voice on Discourse

• Common Voice on Discord

• Common Voice on Telegram

Contribute

• Speak

• Write

• Listen

• Review

Acknowledgements

Datasheet authors

• Emmanuel Ngué Um

Licence

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.

Footnotes

1. 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