Common Voice Spontaneous Speech 2.0 - Betawi

Betawi — Betawi (bew)

This datasheet is for version 2.0 of the the Mozilla Common Voice Spontaneous Speech dataset for Betawi (bew). The dataset contains 1337 clips representing 12 hours of recorded speech (12 hours validated) from 21 speakers.

Language

Betawi language originally belongs to Austronesian language with a full name of Melayu-Betawi. This language is considered as one of Malay dialects, but historically it grew together with other major languages, such as Arabic, Hokkien, Sundanese, Javanese, and Malay in Sumatra - a tiny portion with Portuguese and Dutch. The language vitality status is Endangered according to https://www.ethnologue.com/language/bew/. At the moment, Indonesian standard and English in general influence the native speakers, allowing code switching and code mixing happens in a spontaneous speech. The specific variation of this dataset is Betawi Ora or Betawi Pinggiran (Peripheral Betawi), taken from several locations of Bekasi District/City, West Java Province, Indonesia. This variation is unique in terms of geo-politics: language is spoken only in the community, but it is not taught at school. Instead, the community is taught Sundanese language, which is dominated in West Java Province in general.

Data splits for modelling

Transcriptions

• Prompts: 199

• Duration: 11:54:03 [h:m:s]

• Avg. Transcription Len: 305

• Avg. Duration: 32.04[s]

• Valid Duration: 40109.04[s]

• Total hours: 11.9[h]

• Valid hours: 11.14[h]

The transcription system uses general Latin script, but involves allophone variants of three /e/, these are /é/, /è/, and /e/.

Writing system

Historically, this language used Pegon, Arabic script, but now Latin is adapted.The writing system in this dataset uses general Latin script, but involves allophone variants of three /e/, these are /é/, /è/, and /e/.

Symbol table

a b c d é è ȇ e f g h i j k l m n o p q r s t u v w y z

Samples

Questions

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

Menurut Ente, Kenapé kité musti olahragé rutin?
Begimané cuacé atow musim bikin susé kegiatan seari-ari?
Seperti apé lingkungan nyang cocok bagi Ente?
Di mané Ente tinggal buat masé tué atau pensiun? Kenapé?
Sebutin amé jelasin apé nyang Ente demen di pagi ari?

Responses

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

olahraga rutin ya untuk masa depan juga biar kita tuanya sehat panjang umur pokonyè mentalnya sehat pikirannya sehat olahraga penting si 
cuaca yang êê bikin kegiatan sehari-hari, itu adalah hujan, hujan itu bikin susah semuanya apalagi yang berkendara motor karna kalo ga punya jas hujan itu jadinya ujan-ujanan terutama yang ada daerahnya banjir, karna kalo daerah yang banjir itu otomatis kita tidak akan bisa lêwatin jalanan itu.
Buat saya si lingkungan saya si pengennye tuh ga ada polusi ya kaya, asep kendaraan, ga ada kaya apa tuh jajan-jajanan kimia pengennya tuh ya sejuk gitukan apelagi kalo di pagi hari tu kan udaranya seger kalo di kampung pengennya si hidupnya di kampung aje lah engga banyak polusi.
ayé mah hari tua ayé, ayè hidupnya  dikampung ajê, gampang dikampung mah kaga susêh, bagén katé jauh dari manê-manê dari tempat keramaian, ayê mah tar gè kalo hari tuê, ayê mah pengennya tinggal dikampung ajê udêh ênak, alami, adèm, kaga berisik, banyak pepohonan.
Bangun tidur terus cuci muke, sarapan, abis tu ya masak, nyuci, beberes rumah, nyapu, ngosrek-ngosrek.

Recommended post-processing

(1) Observe the non-linguistic aspects, such as filler, (2) Make sure your machine learning does not differ the suprasegmental aspect, like intonation which does not change the word and its meaning.

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

Get involved!

Community links

• Common Voice translators on Pontoon

• https://referensi.data.kemendikdasmen.go.id/budayakita/wbtb/objek/AA000491

• https://petabahasa.kemdikbud.go.id/ (Web of peta bahasa does not consider Betawi language is part of Indonesia, particularly in Jakarta and West Jawa Province.

Contribute

• Contribute questions

• Validate questions

• Answer questions

• Transcribe recordings

• Validate transcriptions

Acknowledgements

Datasheet authors

• Yacub Fahmilda <yacub.fahmilda@gmail.com>

• Riska Legistari Febri <riskalegistari25@gmail.com>

Funding

This dataset was partially funded by the Open Multilingual Speech Fund managed by Mozilla Common Voice.

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.

Footnotes

1. 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