Common Voice Scripted Speech 25.0 - Batanga
License:
CC0-1.0
Steward:
Common VoiceTask: ASR
Release Date: 3/22/2026
Format: MP3
Size: 321.22 MB
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Description
A collection of read speech recordings in Batanga (bnm).
Specifics
Considerations
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.
Processes
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.
Metadata
bnm — Batanga (bnm)
This datasheet is for cv-corpus-25.0-2026-03-09 of the Mozilla Common Voice Scripted Speech dataset for Batanga [bnm - bnm]. The dataset contains 7943 clips representing 15.82 hours of recorded speech (15.29 hours validated) from 21 speakers, recorded from a text corpus of 1,025 sentences.
Language
Batanga is a coastal Bantu language spoken in the Ocen Division, South Region of Cameroon.
Variants
Contributors to this dataset identified two Batanga dialects: Bapuku and Banoho. Both dialects were used to compile sentence prompts for read speech in the voice clip recordings.
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.
| 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 | 7,943 (100.0%) | 21 (100.0%) |
Gender declared: 0 of 7,943 clips (0.0%), 0 of 21 speakers (0.0%)
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.
| Code | Age | Clips | Speakers |
|---|---|---|---|
| teens | Teens | - | - |
| twenties | Twenties | - | - |
| thirties | Thirties | - | - |
| fourties | Fourties | 478 (6.0%) | 1 (4.8%) |
| fifties | Fifties | 995 (12.5%) | 2 (9.5%) |
| sixties | Sixties | 363 (4.6%) | 1 (4.8%) |
| seventies | Seventies | 994 (12.5%) | 1 (4.8%) |
| eighties | Eighties | - | - |
| nineties | Nineties | - | - |
| - | Unspecified | 5,113 (64.4%) | 20 (95.2%) |
Age declared: 2,830 of 7,943 clips (35.6%), 1 of 21 speakers (4.8%)
Data splits for modelling
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 7,675 (96.6%) |
| Invalidated | 54 (0.7%) |
| Other | 214 (2.7%) |
Training splits
| Split | Clips |
|---|---|
| Train | 412 (5.4%) |
| Dev | 282 (3.7%) |
| Test | 331 (4.3%) |
Training split coverage: 1,025 of 7,675 validated clips (13.4%)
The dataset contains 7675 validated, 54 invalidated, and 214 unresolved clips. The average clip duration is 7.173 seconds.
Text corpus
Validated sentences: 1,025
| Category | Count |
|---|---|
| Unvalidated sentences | - |
| Pending sentences | - |
| Rejected sentences | - |
| Reported sentences | 1 |
The corpus contains 1,025 sentences: 1,025 validated and 0 unvalidated (0 pending review, 0 rejected), with 1 reported for review.
Writing system
The collection of sentence prompts provided by the language representatives aligns with the General Alphabet of Cameroonian Languages
Sample
There follows a randomly selected sample of five sentences from the corpus.
Ilale vi ndɛhɛgi víndi ó idólo vi Bongahɛlɛ.
Bemi bɛ́hɛ́pi bevɔkɔndi nʼkálo mwá etomba.
Medímo mehɔkɔhindini mahulɛ ó nah bato bá benama bayɛ́nɛni myɔ́.
Múna oooh, bandamedɛhɛ, vahe vondi na mʼbana.
Výanga vihapwedɛndi jɛtɔ ó itɔhɔ tɛ́h dá njáhá dí.
Sources
| Source | Sentences |
|---|---|
| Own Submission | 1,025 (100.0%) |
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 userpath- relative path of the audio filetext- supposed transcription of the audioup_votes- number of people who said audio matches the textdown_votes- number of people who said audio does not match textage- age of the speaker1gender- gender of the speaker1accents- accents of the speaker1variant- variant of the language1segment- if sentence belongs to a custom dataset segment, it will be listed hereprompt_upvotes- number of upvotes the sentence prompt receivedprompt_reports- number of reports the sentence prompt receivedis_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 sentencesentence- the sentence textvariant- the variant of the languagesentence_domain- the domain(s) the sentence belongs tosource- the source the sentence was collected fromis_used- whether the sentence is still in circulation for recordingclips_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 sentencesentence- the sentence textvariant- the variant of the languagesentence_domain- the domain(s) the sentence belongs tosource- the source the sentence was collected fromup_votes- number of upvotes the sentence receiveddown_votes- number of downvotes the sentence receivedstatus- current status of the sentence (pendingorrejected)
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Acknowledgements
Datasheet authors
Emmanuel Ngue Um , Jean-Mathieu Etoma , Paul Mpoulet
Citation guidelines
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).
Funding
This dataset was partially funded by the Open Multilingual Speech Fund managed by Mozilla Common Voice.
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
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