Loading datasets...
Release Date: 6/17/2026
Format: MP3
Size: 173.71 MB
Share
A collection of read speech recordings in Kotokoli (kdh).
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.
kdh)This datasheet is for cv-corpus-26.0-2026-06-12 of the Mozilla Common Voice Scripted Speech dataset for Kotokoli [kdh - kdh]. The dataset contains 14207 clips representing 9.66 hours of recorded speech (9.19 hours validated) from 20 speakers, recorded from a text corpus of 1,219 sentences.
Tem (Kotokoli) is a Gur language spoken primarily in Togo, Ghana, Benin, and Burkina Faso. It is part of the Niger-Congo family. The language is used in daily communication, religious practice, and traditional expressions.
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 | - | - |
| female_feminine | Female, feminine | - | - |
| transgender | Transgender | - | - |
| non-binary | Non-binary | - | - |
| do_not_wish_to_say | Prefer not to say | - | - |
| - | Unspecified | 14,207 (100.0%) | 20 (100.0%) |
Gender declared: 0 of 14,207 clips (0.0%), 0 of 20 speakers (0.0%)
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 | 330 (2.3%) | 1 (5.0%) |
| fourties | Fourties | - | - |
| fifties | Fifties | - | - |
| sixties | Sixties | - | - |
| seventies | Seventies | - | - |
| eighties | Eighties | - | - |
| nineties | Nineties | - | - |
| - | Unspecified | 13,877 (97.7%) | 19 (95.0%) |
Age declared: 330 of 14,207 clips (2.3%), 1 of 20 speakers (5.0%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 13,513 (95.1%) |
| Invalidated | 198 (1.4%) |
| Other | 496 (3.5%) |
Training splits
| Split | Clips |
|---|---|
| Train | 498 (3.7%) |
| Dev | 356 (2.6%) |
| Test | 363 (2.7%) |
Training split coverage: 1,217 of 13,513 validated clips (9.0%)
The dataset contains 13513 validated, 198 invalidated, and 496 unresolved clips. The average clip duration is 2.448 seconds.
Validated sentences: 1,219
| Category | Count |
|---|---|
| Unvalidated sentences | - |
| Pending sentences | - |
| Rejected sentences | - |
| Reported sentences | - |
The corpus contains 1,219 sentences: 1,219 validated and 0 unvalidated (0 pending review, 0 rejected), with 0 reported for review.
Tem is a tonal language, typically with two level tones:
High (´)
Low (unmarked)
Tone is essential for distinguishing lexical and grammatical meaning.
Uppercase:
A B C D Ɖ E Ɛ F G Gb H I Ɩ J K Kp L M N Ny Ŋ Ŋm O Ɔ P R S T U Ʊ V W Y Z
Lowercase:
a b c d ɖ e ɛ f g gb h i ɩ j k kp l m n ny ŋ ŋm o ɔ p r s t u ʊ v w y z
There follows a randomly selected sample of five sentences from the corpus.
Digende.
Baadi.
Dingmele.
Izire suuu.
Maluwa nba wanlam bogoobiya zakaa.
The dataset has been compiled from:
Religious books (translations and liturgy).
Dictionaries of Tem.
Common expressions collected from everyday life and fieldwork.
| Source | Sentences |
|---|---|
| self | 1,219 (100.0%) |
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
sentence - the sentence to be read aloud
sentence_id - unique identifier for the sentence
sentence_domain - domain classification(s) of the sentence
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
locale - locale code of the language
segment - if sentence belongs to a custom dataset segment, it will be listed here
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)
Common Voice Tem (kdh) page (link to be activated when available)
Justin Bakoubolo
Bella P.
Justin Bakoubolo — supervised the compilation and coordination of the dataset.
Justin Bakoubolo
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