Common Voice Scripted Speech 25.0 - Indonesian

License:

CC0-1.0

Steward:

Common Voice

Task: ASR

Release Date: 3/22/2026

Format: MP3

Size: 1.42 GB

Description

A collection of read speech recordings in Indonesian (Bahasa Indonesia).

Specifics

Licensing

Creative Commons Zero v1.0 Universal (CC0-1.0)

https://spdx.org/licenses/CC0-1.0.html

Considerations

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.

Processes

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.

Metadata

Bahasa Indonesia — Indonesian (`id`)

This datasheet is for cv-corpus-25.0-2026-03-09 of the Mozilla Common Voice Scripted Speech dataset for Indonesian [Bahasa Indonesia - id]. The dataset contains 60451 clips representing 67.02 hours of recorded speech (33.62 hours validated) from 666 speakers, recorded from a text corpus of 25,182 sentences.

Language

Accents

Code	Accent	Clips	Speakers
-		4,644 (7.7%)	59 (8.9%)

Demographic information

The dataset includes the following self-declared age and gender distributions. A coverage summary is shown below each table.

Gender

Self-declared gender information. The table shows clip and speaker counts with percentages. Speakers who did not declare a gender are listed as Unspecified. A dash (-) indicates zero.

Code	Gender	Clips	Speakers
male_masculine	Male, masculine	26,420 (43.7%)	191 (28.7%)
female_feminine	Female, feminine	15,604 (25.8%)	51 (7.7%)
transgender	Transgender	-	-
non-binary	Non-binary	-	-
do_not_wish_to_say	Prefer not to say	10 (0.0%)	1 (0.2%)
-	Unspecified	18,412 (30.5%)	461 (69.2%)

Gender declared: 42,039 of 60,451 clips (69.5%), 205 of 666 speakers (30.8%)

Age

Self-declared age information. The table shows clip and speaker counts with percentages. Speakers who did not declare an age are listed as Unspecified. A dash (-) indicates zero.

Code	Age	Clips	Speakers
teens	Teens	12,808 (21.2%)	39 (5.9%)
twenties	Twenties	24,964 (41.3%)	157 (23.6%)
thirties	Thirties	6,088 (10.1%)	48 (7.2%)
fourties	Fourties	1,046 (1.7%)	20 (3.0%)
fifties	Fifties	234 (0.4%)	3 (0.5%)
sixties	Sixties	-	-
seventies	Seventies	-	-
eighties	Eighties	-	-
nineties	Nineties	-	-
-	Unspecified	15,311 (25.3%)	443 (66.5%)

Age declared: 45,140 of 60,451 clips (74.7%), 223 of 666 speakers (33.5%)

Data splits for modelling

Clip buckets

Bucket	Clips
Validated	30,331 (50.2%)
Invalidated	2,798 (4.6%)
Other	27,322 (45.2%)

Training splits

Split	Clips
Train	4,975 (16.4%)
Dev	3,469 (11.4%)
Test	3,694 (12.2%)

Training split coverage: 12,138 of 30,331 validated clips (40.0%)

The dataset contains 30331 validated, 2798 invalidated, and 27322 unresolved clips. The average clip duration is 3.991 seconds.

Text corpus

Validated sentences: 13,321

Category	Count
Unvalidated sentences	11,861
Pending sentences	11,848
Rejected sentences	13
Reported sentences	363

The corpus contains 25,182 sentences: 13,321 validated and 11,861 unvalidated (11,848 pending review, 13 rejected), with 363 reported for review.

Sample

There follows a randomly selected sample of five sentences from the corpus.

Tom adalah seorang pemrogram komputer.
Petugas pemadam kebakaran menerobos masuk ke dalam rumah yang sedang terbakar.
Selesai menceritakan kisah ayahnya dengan kota Praha
Ada kalanya hidup itu tidak seindah yang dibayangkan.
Tom menembak Mary dengan senapan.

Sources

Source	Sentences
covost2-en_id	6,465 (48.5%)
sentence-collector	6,240 (46.8%)
http://tatoeba.org	267 (2.0%)
Other	349 (2.6%)

Fields

Clips

Each row of a tsv file represents a single audio clip, and contains the following information:

client_id - hashed UUID of a given user
path - relative path of the audio file
text - supposed transcription of the audio
up_votes - number of people who said audio matches the text
down_votes - number of people who said audio does not match text
age - age of the speaker1
gender - gender of the speaker1
accents - accents of the speaker1
variant - variant of the language1
segment - if sentence belongs to a custom dataset segment, it will be listed here
prompt_upvotes - number of upvotes the sentence prompt received
prompt_reports - number of reports the sentence prompt received
is_edited - whether the clip's transcription has been edited

`validated_sentences.tsv`

The validated_sentences.tsv file contains one row per validated sentence in the text corpus:

sentence_id - unique identifier for the sentence
sentence - the sentence text
variant - the variant of the language
sentence_domain - the domain(s) the sentence belongs to
source - the source the sentence was collected from
is_used - whether the sentence is still in circulation for recording
clips_count - number of clips recorded for this sentence

`unvalidated_sentences.tsv`

The unvalidated_sentences.tsv file contains one row per unvalidated sentence in the text corpus:

sentence_id - unique identifier for the sentence
sentence - the sentence text
variant - the variant of the language
sentence_domain - the domain(s) the sentence belongs to
source - the source the sentence was collected from
up_votes - number of upvotes the sentence received
down_votes - number of downvotes the sentence received
status - current status of the sentence (pending or rejected)

Get involved

Community links

Discussions

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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

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 ↩3 ↩4