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Task: ASR
Release Date: 6/17/2026
Format: MP3
Size: 201.27 MB
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A collection of spontaneous responses to questions in Serian Bidayuh (sdo).
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.
sdo)This datasheet is for sps-corpus-4.0-2026-06-12 of the Mozilla Common Voice Spontaneous Speech dataset for Serian Bidayuh [sdo - sdo]. The dataset contains 1389 clips representing 9.81 hours of recorded speech (1.32 hours validated) from 25 speakers.
The dataset clips are categorised by transcription status and training-set assignment. The following tables summarise the distribution.
| Bucket | Clips | % |
|---|---|---|
| Transcribed & Validated | 217 | 15.6% |
| Transcribed & Pending | 1,172 | 84.4% |
| Not transcribed | 0 | 0.0% |
| Bucket | Clips | % |
|---|---|---|
| Train | 0 | 0.0% |
| Dev | 0 | 0.0% |
| Test | 0 | 0.0% |
| Unassigned | 1,389 | 100.0% |
Training split coverage: 0 of 217 transcribed & validated clips (0.0%)
| Bucket | Clips | % |
|---|---|---|
| Validated | 217 | 15.6% |
| Pending | 1,172 | 84.4% |
| Edited | 493 | 35.5% |
There follows a randomly selected sample of questions used in the corpus.
Tinanen kan ceh masa amu maru r raye ami. Manih bada kayuh ti masu bitetek inyam neh?
What are you proud of? Anih kayuh da maru amu bidangah ti?
Meng anih carab ala ratus nulung inya da susah?
Adehkah mamba amu nanen pasal kisah neh da sani?
Kan amu ira bilajar skil, anih da ira amu bilajar neh?
There follows a randomly selected sample of transcribed responses from the corpus.
Panu da laut da danu nyap aku tapi panu da sungi buleh. Adeh da sungi ti lama dep panu da sungi buleh dep magau bala aaa pane, pane chunto ne bala ungkod kah, bala pakuh sibuk kah aaa adeh ceh da bangih bangih mon ti aaa buleh dep nak ngumbit janik ikan kah anih kah da kadeh mon, ki'uh kah aaa adeh ne da mon. Inang da petpet en, adeh ne da omon.
Inya da patut siken ku kan aku adeh [uhh] manam ti biasa ne aku nyiken neg ande ku sabab dalam pimikir kita ande kita puan simua anih...anih pimanam da pimudip kita... jdi wang aku rasa tibuk aku kaii birapa sihat aku nyiken ande ku taye...kan ande ku manang iti anih simua...kan ne kaii ne dapat [uhh] kenal pasti anih kanam ku ami akan neg klinik la refer dangan doktor.
*Seni, atau art da paling aku suka sien ceh sukan, lukis, pasal pemandangan ataupun sineri ataupun ... dah imaginasi, seni imaginasi dah paling aku suka. *
Movie ato program da paling aku suka sien ceh sukan dangan berita. Berita dunia, berita negara, meng en lagih dangan sukan ato pun dokumentari meng pasal pimudip cuaca da dunia adep dangan da luar dunia. Cuaca dunia la, berita dunia.
Anih teknologi da tinan dep. Teknologi internet sieh mah da tinan adep. Tinan dep kerja, tinan adep lemak magau kayuh, kayuh tinan bala anak adep sikulah pun teknologi internet sieh adep perlu nan dep ngundah kerja.
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