Common Voice Scripted Speech 24.0 - Bafut
License:
CC0-1.0
Steward:
Common VoiceTask: ASR
Release Date: 12/5/2025
Format: MP3
Size: 221.29 MB
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Description
A collection of scripted spoken phrases in Bafut.
Specifics
Considerations
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
[Bafut] — Bafut (bfd)
This datasheet is for version 24.0 of the the Mozilla Common Voice Scripted Speech dataset
for Bafut (bfd). The dataset contains 7180 clips representing 11.27 hours of recorded
speech (10.13 hours validated) from 36 speakers.
Language
Bafut is a Grassfield-Bantu language that belongs to the Ring group, alongside Pinyin, Mankon, Nkwen, Awing, Bambili, Menchum, Babanki, Veŋo, Bamunka, and Wushi. It is spoken in the Mezam and Menchum divisions of the Northwest Region of Cameroon.
Variants
Demographic information
The dataset includes the following distribution of age and gender.
Gender
Self-declared gender information, percentage refers to the number of clips annotated with this gender.
| Gender | Percentage |
|---|---|
| Undefined | 99.0% |
| Female Feminine | 1.0% |
Age
Self-declared age information, percentage refers to the number of clips annotated with this age band.
| Age Band | Percentage |
|---|---|
| Undefined | 99.0% |
| Thirties | 1.0% |
Text corpus
Writing system
The collection of sentence prompts provided by the language representatives aligns with the General Alphabet of Cameroonian Languages
Symbol table
Sample
There follows a randomly selected sample of five sentences from the corpus.
Ŋ̀gwàʼà ɨ fu ghu maʼà
Ǹtsena tswe aa amûm m̀borǝ̀
Mɨ̀nnù ŋû wî mɨ bɨʼɨ mə
A ghɛ̀ɛ nɨ mə̀, kaa mbə mə waʼà gha biì
M̀fɔ̀ Bɨ̀fɨɨ̀ à tswe a tɨtɨ̀ɨ bɨ̀fɔ̀ bîwè fàa mbùʼù àlaʼà
Automatic random samples
Àbà a tswe wa nɨ̂ m̀bî yà yâ.
Ŋ̀gwà à kɨ nɔ̀ʼɔ nɔŋə wa a tweʼe mfɛ̀ʼɛ̀.
Tentə ŋkwee jyâ.
Boma'à neba.
M̀bàŋ jya ɨ lùmə̀.
Sources
Text domains
| Domain | Count |
|---|---|
| Undefined | 7180 |
Processing
Recommended post-processing
Get involved!
Community links
Discussions
Contribute
https://commonvoice.mozilla.org/bfd
Acknowledgements
The compilation of this dataset occured during data camp organized in Yaoundé (Cameroon) in September-October 2024. Two main contributors were involved in the localization of the MCV interface for Bafut, gathering of the sentence prompts, reading sentence prompts, and validating recordings. They are :
Ambe Melvis Lemanka
Ellis Taku Angwa
John Che Ambe
The organization of the data camp was conducted by a dynamic whose dedication is herewith acknowledged :
Eliette Emilie-Caroline Ngo Tjomb Assembe (Project Lead)
Dr. Florus Landry Dibenge
Blaise Mathieu Banoum Manguele
Blaise Abo Djoulde
Mathilde Nyambe A.
Brice Martial Atangana Eloundou
Jeff Sterling Ngami Kamagoua
José Mpuda Avom
Zacharie Nyobe
Emmanuel Giovanni Eloundou Eyenga
André Pascal Likwai
Datasheet authors
Emmanuel Ngue Um ngueum@gmail.com, Ambe Melvis Lemanka melvisleman6@gmail.com, Ellis Taku Angwa takuellis@gmail.com, John Che Ambe <>
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.