Common Voice Scripted Speech 25.0 - Spanish
License:
CC0-1.0
Steward:
Common VoiceTask: ASR
Release Date: 3/24/2026
Format: MP3
Size: 48.23 GB
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Description
A collection of read speech recordings in Spanish (Español).
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
Español — Spanish (es)
This datasheet is for cv-corpus-25.0-2026-03-09 of the Mozilla Common Voice Scripted Speech dataset for Spanish [Español - es]. The dataset contains 1678430 clips representing 2275.15 hours of recorded speech (593.33 hours validated) from 26896 speakers, recorded from a text corpus of 1,087,233 sentences.
Language
Accents
| Code | Accent | Clips | Speakers |
|---|---|---|---|
| mexicano | México | 879,470 (52.4%) | 1,379 (5.1%) |
| surpeninsular | España: Sur peninsular (Andalucia, Extremadura, Murcia) | 177,373 (10.6%) | 260 (1.0%) |
| nortepeninsular | España: Norte peninsular (Asturias, Castilla y León, Cantabria, País Vasco, Navarra, Aragón, La Rioja, Guadalajara, Cuenca) | 66,633 (4.0%) | 634 (2.4%) |
| andino | Andino-Pacífico: Colombia, Perú, Ecuador, oeste de Bolivia y Venezuela andina | 38,723 (2.3%) | 946 (3.5%) |
| centrosurpeninsular | España: Centro-Sur peninsular (Madrid, Toledo, Castilla-La Mancha) | 30,573 (1.8%) | 509 (1.9%) |
| rioplatense | Rioplatense: Argentina, Uruguay, este de Bolivia, Paraguay | 23,500 (1.4%) | 573 (2.1%) |
| caribe | Caribe: Cuba, Venezuela, Puerto Rico, República Dominicana, Panamá, Colombia caribeña, México caribeño, Costa del golfo de México | 21,830 (1.3%) | 581 (2.2%) |
| canario | España: Islas Canarias | 16,193 (1.0%) | 240 (0.9%) |
| americacentral | América central | 12,689 (0.8%) | 376 (1.4%) |
| chileno | Chileno: Chile, Cuyo | 12,569 (0.7%) | 295 (1.1%) |
| filipinas | Español de Filipinas | 606 (0.0%) | 3 (0.0%) |
| - | Other | 6,569 (0.4%) | 224 (0.8%) |
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 | 931,457 (55.5%) | 4,510 (16.8%) |
| female_feminine | Female, feminine | 524,679 (31.3%) | 1,818 (6.8%) |
| transgender | Transgender | - | - |
| non-binary | Non-binary | - | - |
| do_not_wish_to_say | Prefer not to say | 15 (0.0%) | 3 (0.0%) |
| - | Unspecified | 222,279 (13.2%) | 21,276 (79.1%) |
Gender declared: 1,456,151 of 1,678,430 clips (86.8%), 5,620 of 26,896 speakers (20.9%)
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 | 131,769 (7.9%) | 736 (2.7%) |
| twenties | Twenties | 883,187 (52.6%) | 2,924 (10.9%) |
| thirties | Thirties | 155,752 (9.3%) | 1,270 (4.7%) |
| fourties | Fourties | 46,508 (2.8%) | 951 (3.5%) |
| fifties | Fifties | 70,809 (4.2%) | 532 (2.0%) |
| sixties | Sixties | 174,889 (10.4%) | 172 (0.6%) |
| seventies | Seventies | 791 (0.0%) | 28 (0.1%) |
| eighties | Eighties | 246 (0.0%) | 4 (0.0%) |
| nineties | Nineties | 128 (0.0%) | 5 (0.0%) |
| - | Unspecified | 214,351 (12.8%) | 21,040 (78.2%) |
Age declared: 1,464,079 of 1,678,430 clips (87.2%), 5,856 of 26,896 speakers (21.8%)
Data splits for modelling
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 437,718 (26.1%) |
| Invalidated | 95,120 (5.7%) |
| Other | 1,145,592 (68.3%) |
Training splits
| Split | Clips |
|---|---|
| Train | 358,330 (81.9%) |
| Dev | 15,902 (3.6%) |
| Test | 15,902 (3.6%) |
Training split coverage: 390,134 of 437,718 validated clips (89.1%)
The dataset contains 437718 validated, 95120 invalidated, and 1145592 unresolved clips. The average clip duration is 4.88 seconds.
Text corpus
Validated sentences: 1,082,350
| Category | Count |
|---|---|
| Unvalidated sentences | 4,883 |
| Pending sentences | 3,901 |
| Rejected sentences | 982 |
| Reported sentences | 2,644 |
The corpus contains 1,087,233 sentences: 1,082,350 validated and 4,883 unvalidated (3,901 pending review, 982 rejected), with 2,644 reported for review.
Sample
There follows a randomly selected sample of five sentences from the corpus.
Es considerado santo mártir por la Iglesia Ortodoxa de Georgia.
"Los elementos que componen el emblema estatal no están atados a ningún simbolismo ""oficial""."
Así que ahora mismo digo, no, no creo que ese fuera el caso.
Y de altísimo octanaje artístico.
La cola no es de tipo prensil.
Sources
| Source | Sentences |
|---|---|
| wiki | 1,062,101 (98.4%) |
| sentence-collector | 14,245 (1.3%) |
| Other | 3,055 (0.3%) |
Text domains
| Code | Domain | Clips | Speakers |
|---|---|---|---|
| general | General | 46 (0.0%) | 27 (0.1%) |
| agriculture_food | Agriculture and Food | 1 (0.0%) | 1 (0.0%) |
| automotive_transport | Automotive and Transport | 4 (0.0%) | 3 (0.0%) |
| finance | Finance | 6 (0.0%) | 4 (0.0%) |
| service_retail | Service and Retail | 3 (0.0%) | 3 (0.0%) |
| healthcare | Healthcare | 4 (0.0%) | 2 (0.0%) |
| history_law_government | History, Law and Government | 37 (0.0%) | 24 (0.1%) |
| media_entertainment | Media and Entertainment | 8 (0.0%) | 5 (0.0%) |
| nature_environment | Nature and Environment | 12 (0.0%) | 10 (0.0%) |
| news_current_affairs | News and Current Affairs | 19 (0.0%) | 13 (0.0%) |
| technology_robotics | Technology and Robotics | 22 (0.0%) | 11 (0.0%) |
| language_fundamentals | Language Fundamentals | 8 (0.0%) | 5 (0.0%) |
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 userpath- relative path of the audio filetext- supposed transcription of the audioup_votes- number of people who said audio matches the textdown_votes- number of people who said audio does not match textage- age of the speaker1gender- gender of the speaker1accents- accents of the speaker1variant- variant of the language1segment- if sentence belongs to a custom dataset segment, it will be listed hereprompt_upvotes- number of upvotes the sentence prompt receivedprompt_reports- number of reports the sentence prompt receivedis_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 sentencesentence- the sentence textvariant- the variant of the languagesentence_domain- the domain(s) the sentence belongs tosource- the source the sentence was collected fromis_used- whether the sentence is still in circulation for recordingclips_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 sentencesentence- the sentence textvariant- the variant of the languagesentence_domain- the domain(s) the sentence belongs tosource- the source the sentence was collected fromup_votes- number of upvotes the sentence receiveddown_votes- number of downvotes the sentence receivedstatus- current status of the sentence (pendingorrejected)
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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