Common Voice Scripted Speech 25.0 - Batanga

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License:

CC0-1.0

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Steward:

Common Voice

Task: 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

Licensing

Creative Commons Zero v1.0 Universal (CC0-1.0)

https://spdx.org/licenses/CC0-1.0.html

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.

CodeGenderClipsSpeakers
male_masculineMale, masculine--
female_feminineFemale, feminine--
transgenderTransgender--
non-binaryNon-binary--
do_not_wish_to_sayPrefer not to say--
-Unspecified7,943 (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.

CodeAgeClipsSpeakers
teensTeens--
twentiesTwenties--
thirtiesThirties--
fourtiesFourties478 (6.0%)1 (4.8%)
fiftiesFifties995 (12.5%)2 (9.5%)
sixtiesSixties363 (4.6%)1 (4.8%)
seventiesSeventies994 (12.5%)1 (4.8%)
eightiesEighties--
ninetiesNineties--
-Unspecified5,113 (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

BucketClips
Validated7,675 (96.6%)
Invalidated54 (0.7%)
Other214 (2.7%)

Training splits

SplitClips
Train412 (5.4%)
Dev282 (3.7%)
Test331 (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

CategoryCount
Unvalidated sentences-
Pending sentences-
Rejected sentences-
Reported sentences1

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.

  1. Ilale vi ndɛhɛgi víndi ó idólo vi Bongahɛlɛ.

  2. Bemi bɛ́hɛ́pi bevɔkɔndi nʼkálo mwá etomba.

  3. Medímo mehɔkɔhindini mahulɛ ó nah bato bá benama bayɛ́nɛni myɔ́.

  4. Múna oooh, bandamedɛhɛ, vahe vondi na mʼbana.

  5. Výanga vihapwedɛndi jɛtɔ ó itɔhɔ tɛ́h dá njáhá dí.

Sources

SourceSentences
Own Submission1,025 (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 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

Discussions

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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

  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