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Release Date: 9/17/2026
Format: MP3
Size: 227.18 MB
A collection of read speech recordings in Bankon (Ɓàŋkón).
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.
abb)This datasheet is for cv-corpus-27.0-2026-09-11 of the Mozilla Common Voice Scripted Speech dataset for Bankon [Ɓàŋkón - abb]. The dataset contains 7922 clips representing 11.24 hours of recorded speech (11.19 hours validated) from 22 speakers, recorded from a text corpus of 996 sentences.
Bankon, also known as Abo, is a Bantu language spoken in the Moungou Division of Cameroon's Littoral Region. Bakon is closely related to Barombi, also known as Lombi, Balombi, or Barumbi, which is spoken in the Meme Division of the Southwest Region of Cameroon. Therefore, a striking trait that distinguishes the two speech groups is not their intrinsic typological distance, but the colonial demarcation between the French-speaking and English-speaking parts of Cameroon. This is a direct consequence of the joint trusteeship that France and Great Britain held over Cameroon.
The language representatives who contributed to this dataset described Bankon and Barombi (also known as Lombi, Balombi, or Barumbi) as two closely related varieties. However, each is recognized as a distinct language in scientific and administrative nomenclatures. For example, the Administrative Atlas of Cameroon's Languages (Breton and Bikia Fohtung, 1991) recognizes them as such. These representatives added that there are two varieties of Bankon: South Bankon and North Bankon. According to the representatives, however, there are only minor lexical and phonetic differences between these two varieties. Speakers of each variety designate the other variety as Mwi Nwan, wich translates as "the other bank of thhe river". Additionnaly, speakers of South Bakon refer to North Bankon as Bankon Ba Ibom, or "Upper Bankon". Conversely, the speakers of North Bankon refer to South Bankon as Bankon Ba Nlon*, which translates as Lower Bankon. Other less common designations of North Bankon and South Bankon are Banaka and Bayeme, respectively.
Both the Southern and Northern dialects of Bankon are represented in the collection of sentence prompts, with a slight bias towards Southern Bankon.
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 | - | - |
| female_feminine | Female, feminine | - | - |
| transgender | Transgender | - | - |
| non-binary | Non-binary | - | - |
| do_not_wish_to_say | Prefer not to say | - | - |
| - | Unspecified | 7,922 (100.0%) | 22 (100.0%) |
Gender declared: 0 of 7,922 clips (0.0%), 0 of 22 speakers (0.0%)
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 | - | - |
| twenties | Twenties | - | - |
| thirties | Thirties | - | - |
| fourties | Fourties | 20 (0.3%) | 1 (4.5%) |
| fifties | Fifties | - | - |
| sixties | Sixties | - | - |
| seventies | Seventies | - | - |
| eighties | Eighties | - | - |
| nineties | Nineties | - | - |
| - | Unspecified | 7,902 (99.7%) | 22 (100.0%) |
Age declared: 20 of 7,922 clips (0.3%), 0 of 22 speakers (0.0%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 7,887 (99.6%) |
| Invalidated | 35 (0.4%) |
| Other | - |
Training splits
| Split | Clips |
|---|---|
| Train | 390 (4.9%) |
| Dev | 293 (3.7%) |
| Test | 313 (4.0%) |
Training split coverage: 996 of 7,887 validated clips (12.6%)
The dataset contains 7887 validated, 35 invalidated, and 0 unresolved clips. The average clip duration is 5.109 seconds.
Validated sentences: 996
| Category | Count |
|---|---|
| Unvalidated sentences | - |
| Pending sentences | - |
| Rejected sentences | - |
| Reported sentences | - |
The corpus contains 996 sentences: 996 validated and 0 unvalidated (0 pending review, 0 rejected), with 0 reported for review.
The collection of sentence prompts provided by the language representatives aligns with the General Alphabet of Cameroonian Languages
There follows a randomly selected sample of five sentences from the corpus.
Mɛ̌ yèe ndi insāk mu siŋgabìlɛla.
Fìkǎn fi Jɛ̂k fi ta kɛ̀nda ŋgogō yǎ.
Ǹ tǎŋ-kɔ̄m sɔ tɔ̀ màlew i nyū là ǹ nɛɛ̀ wɛ̀.
I pōnda yi maŋgòlò mbyaagɛ yi pǎn iɓaawàk di ŋga᷇n.
Mùt à làke saa ndi cɛ i iɓōŋ di ɓakaala ?
| Source | Sentences |
|---|---|
| Own Submission | 996 (100.0%) |
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)
https://commonvoice.mozilla.org/abb
Emmanuel Ngue Um , Thomas Eyoum Ndando , Emmanuel Ndando , David Miyenga Miyenga
Ngué Um E, Ngo Tjomb EEC, Dibengue FL, Banum Manguele BM, Abo Djoulde B, Nyambe MA, Atangana Eloundou BM, Ngami Kamagoua JS, Mpouda Avom J, Nyobe Z, Eloundou Eyenga EG, Likwai AP (2025) Speech Technologies Datasets for African Under-Served Languages. Proceedings of the Eight Workshop on the Use of Computational Methods in the Study of Endangered Languages, edited by Lachler J, Agyapong G, Arppe A, Moeller S, Chaudhary A, Rijhwani S, Rosenblum D. URL Association for Computational Linguistics (ACL).
This dataset was partially funded by the Open Multilingual Speech Fund managed by Mozilla Common Voice.
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