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Task: ASR
Release Date: 6/17/2026
Format: MP3
Size: 277.94 MB
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A collection of spontaneous responses to questions in Sabah Malay (msi).
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.
msi)This datasheet is for sps-corpus-4.0-2026-06-12 of the Mozilla Common Voice Spontaneous Speech dataset for Sabah Malay [msi - msi]. The dataset contains 2277 clips representing 13.54 hours of recorded speech (0.01 hours validated) from 33 speakers.
The dataset clips are categorised by transcription status and training-set assignment. The following tables summarise the distribution.
| Bucket | Clips | % |
|---|---|---|
| Transcribed & Validated | 4 | 0.2% |
| Transcribed & Pending | 2,273 | 99.8% |
| Not transcribed | 0 | 0.0% |
| Bucket | Clips | % |
|---|---|---|
| Train | 0 | 0.0% |
| Dev | 0 | 0.0% |
| Test | 0 | 0.0% |
| Unassigned | 2,277 | 100.0% |
Training split coverage: 0 of 4 transcribed & validated clips (0.0%)
| Bucket | Clips | % |
|---|---|---|
| Validated | 4 | 0.2% |
| Pending | 2,273 | 99.8% |
| Edited | 3 | 0.1% |
There follows a randomly selected sample of questions used in the corpus.
Apa sebab utama orang dalam komuniti kamu berpindah ke tempat lain?
Apa iklim tempat tinggal kamu?
Terangkan peristiwa bersejarah yang kamu pelajari di sekolah
Adakah terdapat sekeping kerja rumah yang kamu ingat bergelut dengannya?
Siapa artis atau tukang tempatan yang kamu kagumi?
There follows a randomly selected sample of transcribed responses from the corpus.
[Um] Ini tentang [Um] bersistem sokongan sosial yang disediakan oleh kerajaan [Um] agak baik dan berkesan untuk memudahkan [Um] masyarakat.
Ini setiap hari, menyimak [Um] tugasan, menyimak [Um] apa [Um] hantar-hantaran daripada [unclear] [Um] itu setiap hari [noise] [Um] lebih daripada 10 kali sehari.
*Kalau pemuzik atau penulis lagu kegemaran saya ialah M Nasir M Nasir saya lebih gemar mendengar lagu-lagu M Nasir [noise]. *
*Buat masa sekarang ni [Um] teknologi yang [Um] merisaukan saya ialah berkaitan dengan [Um] ni data ni contohnya "handphone" data "handphone" [Um] sebab kalau ini lah peluang untuk "scammer-scammer" akan buat masuk sini sebab kalau kita punya data sudah terlepas di tangan dorang jadi itu yang saya akan rasa risau [Um]. *
Salah satunya [Um] yang paling utama [Um] macam mana negara kita ni dapat mencapai kemerdekaanlah [Um] itu salah satu peristiwa sejarah yang sememangnya akan dipelajari oleh masyarakat di nega-negara ini macam mana usaha dorang [Um] macam mana dorang buat apa yang dorang suda janji apa yang dorang suda [Um] lakukan dari tahun ini tahun sampai tahun-tahun sembilan belas lima puluh tujuh sampai dorang dapat kemerdekaan.
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