Common Voice Spontaneous Speech 1.0 - Sabah Malay

Sabah Malay — Sabah Malay (`msi`)

This datasheet has been generated automatically, we would love to include more information, if you would like to help out, get in touch!

This datasheet is for version 23.0 of the the Mozilla Common Voice Spontaneous Speech dataset for Sabah Malay (msi). The dataset contains 2301 clips representing 14 hours of recorded speech (1 hours validated) from 33 speakers.

Demographic information

The dataset includes the following distribution of age and gender.

Gender

Self-declared gender information, frequency refers to the number of clips annotated with this gender.

Age

Self-declared age information, frequency refers to the number of clips annotated with this age band.

Data splits for modelling

Split	Count
Train	1747
Test	269
Dev	285

Transcriptions

Prompts: 119
Duration: 49222512[ms]
Avg. Transcription Len: 218
Avg. Duration: 21.39[s]
Valid Duration: 70.02[s]
Total hours: 13.67[h]
Valid hours: 0.02[h]

Questions

There follows a randomly selected sample of questions used in the corpus.

Apa keinginan kamu untuk anak-anak kamu?
Dengan cara apa yang kamu  pikir teknologi boleh disepadukan dengan lebih baik ke dalam pendidikan?
Apa keadaan awan di tempat tinggal kamu?
Kamu tahukah apa nama bintang dan buruj?
Bagaimana kamu berehat dan menjaga minda yang sihat?

Responses

There follows a randomly selected sample of transcribed responses from the corpus.

[noise] [um] Saya dua-dua, saya suka berada dalam rumah dan juga diluar rumah [um] sebab aktiviti saya memang ada jadi kena ada dalam rumah dan juga di luar rumah [noise].
"[um] Selalu kami atau pun saya gunakan teknologi yang ada sekarang ini ialah menggunakan telefon atau pun ""handphone"" yang memudahkan urusan."
[noise] Ya, [um] kita kalau masuk ke dalam pawagam, pertama kita melihat kebersihannya dan kita melihat [um] cerita yang ditayangkan. Jadi kerana itu baru kita mahu menonton [um] apa-apa filem dalam pawagam.
Kalau bahasa yang mempelajari bahasa yang dituturkan ini [um] saya rasa [um] itu daripada kami sendiri lah, kalau di Sabah ini [um] macam mana sebab bahasa melayu Sabah kami punya standard melayu Sabah lah.
Ok dalam budaya kami ubat-ubatan tradisional yang wujud antaranya menggunakan tumbuh tumbuhan atau pun [um] ataupun tapi lebih kepada tumbuh-tumbuhan lah contohnya macam daun-daun yang boleh dibuat ubat.

Fields

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 30 seconds

Community links

Common Voice translators on Pontoon

Contribute

Licence

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 demograpics spec. These will only be reported if the speaker opted in to provide that information. ↩ ↩²