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Task: ASR
Release Date: 3/24/2026
Format: MP3
Size: 48.23 GB
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A collection of read speech recordings in Spanish (Español).
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.
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.
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.
| 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%) |
The dataset includes the following self-declared age and gender distributions. A coverage summary is shown below each table.
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%)
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%)
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.
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.
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.
| Source | Sentences |
|---|---|
| wiki | 1,062,101 (98.4%) |
| sentence-collector | 14,245 (1.3%) |
| Other | 3,055 (0.3%) |
| 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%) |
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.tsvThe 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.tsvThe 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)
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.
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