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Task: ASR
Release Date: 6/17/2026
Format: MP3
Size: 365.90 MB
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A collection of spontaneous responses to questions in Ruuli (ruc).
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.
ruc)This datasheet is for sps-corpus-4.0-2026-06-12 of the Mozilla Common Voice Spontaneous Speech dataset for Ruuli [ruc - ruc]. The dataset contains 2822 clips representing 17.75 hours of recorded speech (10.14 hours validated) from 26 speakers.
The dataset clips are categorised by transcription status and training-set assignment. The following tables summarise the distribution.
| Bucket | Clips | % |
|---|---|---|
| Transcribed & Validated | 1,659 | 58.8% |
| Transcribed & Pending | 0 | 0.0% |
| Not transcribed | 1,163 | 41.2% |
| Bucket | Clips | % |
|---|---|---|
| Train | 1,046 | 37.1% |
| Dev | 359 | 12.7% |
| Test | 254 | 9.0% |
| Unassigned | 1,163 | 41.2% |
Training split coverage: 1,659 of 1,659 transcribed & validated clips (100.0%)
| Bucket | Clips | % |
|---|---|---|
| Validated | 1,659 | 100.0% |
| Pending | 0 | 0.0% |
| Edited | 181 | 10.9% |
There follows a randomly selected sample of questions used in the corpus.
Ebyanyegeesya bikoore mulimuki edi ekka ezanjawulo omukulakulanya ebuzinensi zabulizo oba amakooro?
Ngeriki ebyanyegeesya jebinduireemu obwoomi bwamu?
Enkola yabyanyegesya eiziire etumbuka etyai okukyalo kyamu emyaka ejakaire?
Okoleserye otyai obwegeesye bwamu okwirirya ekintundu kyamu?
Mulimu ki ekyalo kyamu kyegukoore okuyambaku abeegi neʼkka zabwe omubyanyegeesya?
There follows a randomly selected sample of transcribed responses from the corpus.
*Omu bifo ebyanjawulo abantu ba mweka yange gyini gyebakaire nka masomero nebega nibabangulwa begere empisa takuba amwei begere empisa yakwatagana nokukllagana amwei nabantu omu kitundu kale ebyanyegesya nibyo biyambire okwika okweco *
*Ebyanyegesya engeri gyebiyambire ku ekyukakyuka omweka yange budi twamanyanga nti abaana ba bwala tebasoma naye buni abaana ba bwala bakusoma buni bakusomeserye okuba n'obutandalo ekka okuba no toilet okuba ne kyina kya kasasiro so byona byona tubyetejere oku lwa nyegesya *
*Engeri ekusooka omwana oyo obubona nga tayina kusai maani omutwala omudwaliro nibaba nga bakumuwerya e vitamin ekumala oba naba nga teyagemeibwe omutwala omwana oyo natandika okuba nga agemembwa akufuna e vitamin zamwei kusai *
Aa okwaba okwekeberesya omwirwaro kisigikira naye nga ebiseera ebisinga oyakalyawo emyezi isatu buli luzwanyuma lwa myezi isatu noyaba nibakkebera okubona ka noyemereire ate te nokuteeka omunkola ekyo abasawu kibakunyonyoire oluzwannyuma lwa kukebera okumanya embeera gyoyemereiremu osobole okubba n'obwomi obusai.
*Aaa engeri nensumbamu ecibulo kyensinga okwendya aaa nimbanga ndina ecibulo kyentekeretekere cinkwakusumba aaa ny'etaku emikwano jange aaa ninkoba bairange ninawo ecibulo kyentekeretekere naye nkwendya kumpa kumagezi nitwikaara aa emikwano jange nijimpa amagezi nitukola ebajeeti oluvanyuma aaa neko nituwa nenaku zamwezi netusobola okuba nga okulunaku olwo tukusumba ekibulo nituliira amwei nemikwago jange nabantu abandi eyo niyo ngeri jenyinza okusumbamu ecibulo kyensinga okwendya. *
Each row of a tsv file represents a single audio clip, and contains the following information:
client_id - hashed UUID of a given user
audio_id - numeric id for audio file
audio_file - audio file name
duration_ms - duration of audio in milliseconds
prompt_id - numeric id for prompt
prompt - question for user
transcription - transcription of the audio response
votes - number of people that who approved a given transcript
age - age of the speaker1
gender - gender of the speaker1
language - language name
split - for data modelling, which subset of the data does this clip pertain to
char_per_sec - how many characters of transcription per second of audio
quality_tags - some automated assessment of the transcription--audio pair, separated by |
transcription-length - character per second under 3 characters per second
speech-rate - characters per second over 30 characters per second
short-audio - audio length under 2 seconds
long-audio - audio length over 5 minutes
non-allowed-script - transcription contains characters from a writing system not associated with the language
mixed-script-words - a single word contains characters from multiple writing systems
mixed-script-transcription - transcription spans multiple writing systems, but each word consistently uses only one
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