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Task: ASR
Release Date: 3/22/2026
Format: MP3
Size: 526.61 MB
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A collection of read speech recordings in Dagbani (Dagbanli).
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.
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.
According to Ethnologue online, Dagbani is a stable indigenous language of Ghana. It belongs to the Niger-Congo language family.
| Code | Accent | Clips | Speakers |
|---|---|---|---|
| - | 136 (0.6%) | 5 (7.2%) |
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 | 428 (1.9%) | 2 (2.9%) |
| female_feminine | Female, feminine | 4,549 (19.7%) | 13 (18.8%) |
| transgender | Transgender | - | - |
| non-binary | Non-binary | - | - |
| do_not_wish_to_say | Prefer not to say | 415 (1.8%) | 1 (1.4%) |
| - | Unspecified | 17,694 (76.6%) | 57 (82.6%) |
Gender declared: 5,392 of 23,086 clips (23.4%), 12 of 69 speakers (17.4%)
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 | 9,308 (40.3%) | 20 (29.0%) |
| thirties | Thirties | 5,842 (25.3%) | 19 (27.5%) |
| fourties | Fourties | 241 (1.0%) | 1 (1.4%) |
| fifties | Fifties | - | - |
| sixties | Sixties | - | - |
| seventies | Seventies | - | - |
| eighties | Eighties | - | - |
| nineties | Nineties | - | - |
| - | Unspecified | 7,695 (33.3%) | 40 (58.0%) |
Age declared: 15,391 of 23,086 clips (66.7%), 29 of 69 speakers (42.0%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 13,596 (58.9%) |
| Invalidated | 256 (1.1%) |
| Other | 9,234 (40.0%) |
Training splits
| Split | Clips |
|---|---|
| Train | 1,610 (11.8%) |
| Dev | 1,465 (10.8%) |
| Test | 1,464 (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.
Validated sentences: 5,603
| Category | Count |
|---|---|
| Unvalidated sentences | 15,134 |
| Pending sentences | 15,034 |
| Rejected sentences | 100 |
| Reported sentences | 23 |
The corpus contains 20,737 sentences: 5,603 validated and 15,134 unvalidated (15,034 pending review, 100 rejected), with 23 reported for review.
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.
There follows a randomly selected sample of five sentences from the corpus.
Ka ŋuni n-lee yɛn zaŋ buɣilimbuɣiliŋ maa n-yili jaŋkuno maa nyiŋgoli ni?
bina ayi maa ni dini n-lee gari di kpee?
Di ŋmεri ya namgban kpeeni n sani.
Azindoo ŋun yurila bin'gula gulibu.
Nyini n-nyɛ o nyaandola.
| Source | Sentences |
|---|---|
| Originally fromTony Baden's Dagbani Dictionary and compiled with permission by members of the Dagbani Wikimedians User Group | 2,256 (40.3%) |
| Dagbani Wikimedia Community | 2,254 (40.2%) |
| Own Submission | 1,074 (19.2%) |
| Other | 19 (0.3%) |
| Code | Domain | Clips | Speakers |
|---|---|---|---|
| general | General | 23 (0.1%) | 16 (23.2%) |
| agriculture_food | Agriculture and Food | 4 (0.0%) | 4 (5.8%) |
| automotive_transport | Automotive and Transport | 3 (0.0%) | 3 (4.3%) |
| finance | Finance | 13 (0.1%) | 13 (18.8%) |
| service_retail | Service and Retail | - | - |
| healthcare | Healthcare | - | - |
| history_law_government | History, Law and Government | - | - |
| media_entertainment | Media and Entertainment | - | - |
| nature_environment | Nature and Environment | 6 (0.0%) | 6 (8.7%) |
| news_current_affairs | News and Current Affairs | 4 (0.0%) | 4 (5.8%) |
| technology_robotics | Technology and Robotics | - | - |
| language_fundamentals | Language Fundamentals | 3 (0.0%) | 3 (4.3%) |
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.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/dag/
Emmanuel Ngue Um , Osman Mohammed Nndow , Hadja Natuusamata Abubakari .
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