Common Voice Spontaneous Speech 3.0 - Catalan
License:
CC0-1.0
Steward:
Common VoiceTask: ASR
Release Date: 3/22/2026
Format: MP3
Size: 13.32 MB
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Description
A collection of spontaneous responses to questions in Catalan (català).
Specifics
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
català — Catalan (ca)
This datasheet is for sps-corpus-3.0-2026-03-09 of the Mozilla Common Voice Spontaneous Speech dataset for Catalan [català - ca]. The dataset contains 149 clips representing 0.65 hours of recorded speech (0.49 hours validated) from 15 speakers.
Language
Catalan is a Romance language spoken by about 9 milion people mainly on the Mediterranean coast of the Iberian Peninsula.
It is an official language, along with Spanish or Castilian, in Catalonia, the Balearic Islands and the Valencian Community (where it is also called Valencian), while it is the only official language of the Principality of Andorra. It is also spoken, and has some administrative recognition, without reaching official status, in the eastern part of the autonomous community of Aragon, in the French department Pyrénées-Orientales (Eastern Pyrenees) and in the city of Alghero, on the island of Sardinia (Italy).
The language evolved from Vulgar Latin in the Middle Ages.
Variants
The main variants of Catalan are:
Central [ca-central]: It is the variant with the most speakers, as it encompasses the metropolitan area of Barcelona, extending to the region of Girona and the eastern half of Tarragona
Balearic [ca-balear]: The variant used in the Balearic Islands
Nord-Occidental [ca-nwestern]: Spoken in Andorra, Lleida and the western half of Tarragona in Catalonia, and the eastern part of Aragon
Septentrional [ca-northern]: Corresponds to the area of Roussillon and the northern part of Girona
Valencian: Spoken in the Valencian comunity, where it's also known as "Valencian"
Valencià meridional [ca-valencia-southern]
Alacantí [ca-valencia-alacant]
Valencià septentrional [ca-valencia-northern]
Tortosí [ca-valencia-tortosi]
Valencià central [ca-valencia-central]
Alguerese [ca-algueres]: Spoken in the city of Alghero, in Sardinia
Data splits for modelling
The dataset clips are categorised by transcription status and training-set assignment. The following tables summarise the distribution.
Audio clips
| Bucket | Clips | % |
|---|---|---|
| Transcribed & Validated | 123 | 82.6% |
| Transcribed & Pending | 19 | 12.8% |
| Not transcribed | 7 | 4.7% |
Training splits
| Bucket | Clips | % |
|---|---|---|
| Train | 0 | 0.0% |
| Dev | 0 | 0.0% |
| Test | 0 | 0.0% |
| Unassigned | 149 | 100.0% |
Training split coverage: 0 of 123 transcribed & validated clips (0.0%)
Transcriptions
Transcription status
| Bucket | Clips | % |
|---|---|---|
| Validated | 123 | 86.6% |
| Pending | 19 | 13.4% |
| Edited | 42 | 29.6% |
Writing system
Catalan is written using the Latin alphabet (abcdefghijklmnopqrstuvwxyz), with the special characters ç and l·l. In addition, vowels can be accented (à, è, é, í, ò, ó, ú, ü, ï). The characters - (hyphen) and ' (apostrophe) are also part of Catalan orthography.
Symbol table
a b c ç d e f g h i j k l m n o p q r s t u v w x y z à è é í ò ó ú ï ü
Samples
Questions
There follows a randomly selected sample of questions used in the corpus.
Quina tasca de voluntariat tʼagradaria provar i per què?
Què significa lʼèxit per a tu?
Quina és la teva festa preferida i per què?
Quins elements fan que un petit comerç local et resulti especialment atractiu?
Com valores el fet de fer la migdiada els caps de setmana?
Responses
There follows a randomly selected sample of transcribed responses from the corpus.
Mira, em el trobo d'un, diguem, el que a mi m'emociona dels castells, perquè en allà veig alguna cosa preciosa que fem entre tots, és allà un un individu allà és rellevant, la importància, el castell, esdevé quan tots nem...
Les ganes de fer vacances
De tot. M'encanta aprendre. M'agradaria molt aprendre més coses i tenir temps per aprendre més coses. Ja tinc una certa edat i, ara estic aprenent italià, que és una llengua que m'agrada molt i, penso que, quan em jubili, una part del temps que guanyaré el dedicaré a aprendre encara més coses. Com que soc més de lletres, doncs, segurament seran, jo que sé, noves llengües o, m'apuntaré a cursos o a seminaris d'història que m'ha és el que més m'ha agradat a la vida i és el que he estudiat o eh, no ho sé, coses així: música... Però, segur, segur que dedicaré molt de temps a seguir aprenent. Penso que és essencial durant la vida aprendre fins al final.
Diria que l'amabilitat i el tracte dels comerciants, també el coneixement mutu que es pot tindre quan és un xicotet comerç entre el comercial i el client i... pense que també és important la varietat i tindre preus raonables.
Molta gent comprant al voltant de les botigues, parlant entre ells.
Recommended post-processing
It is recommended to normalize instances of the geminate L, which can take the equivalent forms of l·l or ŀl.
Fields
Each row of a tsv file represents a single audio clip, and contains the following information:
client_id- hashed UUID of a given useraudio_id- numeric id for audio fileaudio_file- audio file nameduration_ms- duration of audio in millisecondsprompt_id- numeric id for promptprompt- question for usertranscription- transcription of the audio responsevotes- number of people that who approved a given transcriptage- age of the speaker1gender- gender of the speaker1language- language namesplit- for data modelling, which subset of the data does this clip pertain tochar_per_sec- how many characters of transcription per second of audioquality_tags- some automated assessment of the transcription--audio pair, separated by|transcription-length- character per second under 3 characters per secondspeech-rate- characters per second over 30 characters per secondshort-audio- audio length under 2 secondslong-audio- audio length over 5 minutes
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Acknowledgements
Datasheet authors
Carme Armentano <carme.armentano@bsc.es>
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