Common Voice Scripted Speech 25.0 - Sardinian

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License:

CC0-1.0

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Steward:

Common Voice

Task: ASR

Release Date: 3/22/2026

Format: MP3

Size: 73.61 MB


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Description

A collection of read speech recordings in Sardinian (Sardu).

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

Sardu — Sardinian (sc)

This datasheet is for cv-corpus-25.0-2026-03-09 of the Mozilla Common Voice Scripted Speech dataset for Sardinian [Sardu - sc]. The dataset contains 2822 clips representing 3.68 hours of recorded speech (3.01 hours validated) from 43 speakers, recorded from a text corpus of 5,838 sentences.

Language

Accents

CodeAccentClipsSpeakers
-1,408 (49.9%)10 (23.3%)

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.

CodeGenderClipsSpeakers
male_masculineMale, masculine347 (12.3%)3 (7.0%)
female_feminineFemale, feminine933 (33.1%)3 (7.0%)
transgenderTransgender--
non-binaryNon-binary--
do_not_wish_to_sayPrefer not to say--
-Unspecified1,542 (54.6%)41 (95.3%)

Gender declared: 1,280 of 2,822 clips (45.4%), 2 of 43 speakers (4.7%)

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.

CodeAgeClipsSpeakers
teensTeens--
twentiesTwenties255 (9.0%)2 (4.7%)
thirtiesThirties799 (28.3%)4 (9.3%)
fourtiesFourties32 (1.1%)1 (2.3%)
fiftiesFifties414 (14.7%)2 (4.7%)
sixtiesSixties47 (1.7%)2 (4.7%)
seventiesSeventies--
eightiesEighties--
ninetiesNineties--
-Unspecified1,275 (45.2%)37 (86.0%)

Age declared: 1,547 of 2,822 clips (54.8%), 6 of 43 speakers (14.0%)

Data splits for modelling

Clip buckets

BucketClips
Validated2,306 (81.7%)
Invalidated120 (4.3%)
Other396 (14.0%)

Training splits

SplitClips
Train926 (40.2%)
Dev554 (24.0%)
Test652 (28.3%)

Training split coverage: 2,132 of 2,306 validated clips (92.5%)

The dataset contains 2306 validated, 120 invalidated, and 396 unresolved clips. The average clip duration is 4.705 seconds.

Text corpus

Validated sentences: 5,489

CategoryCount
Unvalidated sentences349
Pending sentences346
Rejected sentences3
Reported sentences36

The corpus contains 5,838 sentences: 5,489 validated and 349 unvalidated (346 pending review, 3 rejected), with 36 reported for review.

Sample

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

  1. Sa giustìtzia andat a dae in antis.

  2. Sos contos, inèditos e in italianu, devent «apassionare sos minores a sa letura».

  3. Ma non pro issu.

  4. Mègius a fraigare retzes cun àteros grupos e movimentos.

  5. Fatu est giai su passu; càllia!

Sources

SourceSentences
sentence-collector5,231 (95.3%)
Laboratòriu INSULAS135 (2.5%)
Other123 (2.2%)

Text domains

CodeDomainClipsSpeakers
generalGeneral9 (0.3%)6 (14.0%)
agriculture_foodAgriculture and Food2 (0.1%)1 (2.3%)
automotive_transportAutomotive and Transport1 (0.0%)1 (2.3%)
financeFinance1 (0.0%)1 (2.3%)
service_retailService and Retail--
healthcareHealthcare2 (0.1%)2 (4.7%)
history_law_governmentHistory, Law and Government--
media_entertainmentMedia and Entertainment1 (0.0%)1 (2.3%)
nature_environmentNature and Environment1 (0.0%)1 (2.3%)
news_current_affairsNews and Current Affairs3 (0.1%)2 (4.7%)
technology_roboticsTechnology and Robotics--
language_fundamentalsLanguage Fundamentals--

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)

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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

  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 3 4