Common Voice Scripted Speech 25.0 - Dagbani

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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: 526.61 MB


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Description

A collection of read speech recordings in Dagbani (Dagbanli).

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

Dagbanli — Dagbani (dag)

This datasheet is for cv-corpus-25.0-2026-03-09 of the Mozilla Common Voice Scripted Speech dataset for Dagbani [Dagbanli - dag]. The dataset contains 23086 clips representing 27.53 hours of recorded speech (16.21 hours validated) from 69 speakers, recorded from a text corpus of 20,737 sentences.

Language

According to Ethnologue online, Dagbani is a stable indigenous language of Ghana. It belongs to the Niger-Congo language family.

Accents

CodeAccentClipsSpeakers
-136 (0.6%)5 (7.2%)

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, masculine428 (1.9%)2 (2.9%)
female_feminineFemale, feminine4,549 (19.7%)13 (18.8%)
transgenderTransgender--
non-binaryNon-binary--
do_not_wish_to_sayPrefer not to say415 (1.8%)1 (1.4%)
-Unspecified17,694 (76.6%)57 (82.6%)

Gender declared: 5,392 of 23,086 clips (23.4%), 12 of 69 speakers (17.4%)

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--
twentiesTwenties9,308 (40.3%)20 (29.0%)
thirtiesThirties5,842 (25.3%)19 (27.5%)
fourtiesFourties241 (1.0%)1 (1.4%)
fiftiesFifties--
sixtiesSixties--
seventiesSeventies--
eightiesEighties--
ninetiesNineties--
-Unspecified7,695 (33.3%)40 (58.0%)

Age declared: 15,391 of 23,086 clips (66.7%), 29 of 69 speakers (42.0%)

Data splits for modelling

Clip buckets

BucketClips
Validated13,596 (58.9%)
Invalidated256 (1.1%)
Other9,234 (40.0%)

Training splits

SplitClips
Train1,610 (11.8%)
Dev1,465 (10.8%)
Test1,464 (10.8%)

Training split coverage: 4,539 of 13,596 validated clips (33.4%)

The dataset contains 13596 validated, 256 invalidated, and 9234 unresolved clips. The average clip duration is 4.294 seconds.

Text corpus

Validated sentences: 5,603

CategoryCount
Unvalidated sentences15,134
Pending sentences15,034
Rejected sentences100
Reported sentences23

The corpus contains 20,737 sentences: 5,603 validated and 15,134 unvalidated (15,034 pending review, 100 rejected), with 23 reported for review.

Writing system

The collection of sentence prompts used for read speech in the compilation of this dataset was scripted with in an alphabet that is mostly based on Latin characgers with some phonetic symbols such as ɣ, ʒ, ŋ, ɛ, and ɔ.

Sample

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

  1. Ka ŋuni n-lee yɛn zaŋ buɣilimbuɣiliŋ maa n-yili jaŋkuno maa nyiŋgoli ni?

  2. bina ayi maa ni dini n-lee gari di kpee?

  3. Di ŋmεri ya namgban kpeeni n sani.

  4. Azindoo ŋun yurila bin'gula gulibu.

  5. Nyini n-nyɛ o nyaandola.

Sources

SourceSentences
Originally fromTony Baden's Dagbani Dictionary and compiled with permission by members of the Dagbani Wikimedians User Group2,256 (40.3%)
Dagbani Wikimedia Community2,254 (40.2%)
Own Submission1,074 (19.2%)
Other19 (0.3%)

Text domains

CodeDomainClipsSpeakers
generalGeneral23 (0.1%)16 (23.2%)
agriculture_foodAgriculture and Food4 (0.0%)4 (5.8%)
automotive_transportAutomotive and Transport3 (0.0%)3 (4.3%)
financeFinance13 (0.1%)13 (18.8%)
service_retailService and Retail--
healthcareHealthcare--
history_law_governmentHistory, Law and Government--
media_entertainmentMedia and Entertainment--
nature_environmentNature and Environment6 (0.0%)6 (8.7%)
news_current_affairsNews and Current Affairs4 (0.0%)4 (5.8%)
technology_roboticsTechnology and Robotics--
language_fundamentalsLanguage Fundamentals3 (0.0%)3 (4.3%)

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

Contribute

https://commonvoice.mozilla.org/dag/

Acknowledgements

Datasheet authors

Emmanuel Ngue Um , Osman Mohammed Nndow , Hadja Natuusamata Abubakari .

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