hamayawayuri/common-voice-26-en-audio

English — English (en)

This datasheet is for cv-corpus-26.0-2026-06-12 of the Mozilla Common Voice Scripted Speech dataset for English [English - en]. The dataset contains 2583051 clips representing 3780.95 hours of recorded speech (2784.88 hours validated) from 100172 speakers, recorded from a text corpus of 1,721,897 sentences.

Language

English is a West Germanic language with origins in England. There are an estimated 1.5 billion English speakers, making it the most widely spoken language in the world. English is commonly learned as a second language in many countries.

Accents

Code	Accent	Clips	Speakers
us	United States English	573,393 (22.2%)	10,970 (11.0%)
england	England English	204,106 (7.9%)	3,445 (3.4%)
indian	India and South Asia (India, Pakistan, Sri Lanka)	152,723 (5.9%)	3,029 (3.0%)
canada	Canadian English	101,061 (3.9%)	1,220 (1.2%)
australia	Australian English	69,363 (2.7%)	948 (0.9%)
scotland	Scottish English	68,131 (2.6%)	270 (0.3%)
african	Southern African (South Africa, Zimbabwe, Namibia)	60,292 (2.3%)	441 (0.4%)
newzealand	New Zealand English	20,768 (0.8%)	230 (0.2%)
ireland	Irish English	11,204 (0.4%)	266 (0.3%)
philippines	Filipino	7,492 (0.3%)	207 (0.2%)
hongkong	Hong Kong English	7,004 (0.3%)	190 (0.2%)
singapore	Singaporean English	4,722 (0.2%)	112 (0.1%)
malaysia	Malaysian English	4,235 (0.2%)	154 (0.2%)
wales	Welsh English	3,032 (0.1%)	119 (0.1%)
bermuda	West Indies and Bermuda (Bahamas, Bermuda, Jamaica, Trinidad)	1,231 (0.0%)	74 (0.1%)
southatlandtic	South Atlantic (Falkland Islands, Saint Helena)	332 (0.0%)	9 (0.0%)
other	Other	200,693 (7.8%)	1,681 (1.7%)

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	1,117,432 (43.3%)	18,517 (18.5%)
female_feminine	Female, feminine	457,904 (17.7%)	5,563 (5.6%)
transgender	Transgender	156 (0.0%)	11 (0.0%)
non-binary	Non-binary	411 (0.0%)	17 (0.0%)
do_not_wish_to_say	Prefer not to say	2,009 (0.1%)	44 (0.0%)
-	Unspecified	1,004,989 (38.9%)	78,307 (78.2%)

Gender declared: 1,578,062 of 2,583,051 clips (61.1%), 21,865 of 100,172 speakers (21.8%)

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	151,296 (5.9%)	3,255 (3.2%)
twenties	Twenties	641,400 (24.8%)	11,552 (11.5%)
thirties	Thirties	357,504 (13.8%)	5,369 (5.4%)
fourties	Fourties	240,835 (9.3%)	2,651 (2.6%)
fifties	Fifties	136,070 (5.3%)	1,590 (1.6%)
sixties	Sixties	115,750 (4.5%)	915 (0.9%)
seventies	Seventies	17,522 (0.7%)	365 (0.4%)
eighties	Eighties	2,427 (0.1%)	55 (0.1%)
nineties	Nineties	306 (0.0%)	12 (0.0%)
-	Unspecified	919,941 (35.6%)	76,964 (76.8%)

Age declared: 1,663,110 of 2,583,051 clips (64.4%), 23,208 of 100,172 speakers (23.2%)

Data splits for modelling

Clip buckets

Bucket	Clips
Validated	1,902,564 (73.7%)
Invalidated	313,382 (12.1%)
Other	367,105 (14.2%)

Training splits

Split	Clips
Train	1,147,812 (60.3%)
Dev	16,403 (0.9%)
Test	16,403 (0.9%)

Training split coverage: 1,180,618 of 1,902,564 validated clips (62.1%)

The dataset contains 1902564 validated, 313382 invalidated, and 367105 unresolved clips. The average clip duration is 5.27 seconds.

Text corpus

Validated sentences: 1,681,666

Category	Count
Unvalidated sentences	40,231
Pending sentences	36,278
Rejected sentences	3,953
Reported sentences	9,773

The corpus contains 1,721,897 sentences: 1,681,666 validated and 40,231 unvalidated (36,278 pending review, 3,953 rejected), with 9,773 reported for review.

Writing system

The English writing system is based off of the latin alphabet.

Symbol table

a b c d e f g h i j k l m n o p q r s t u v w x y z

Sample

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

1. For example, a heavily rhythmic speech filled with mnemonic devices enhances memory and recall.
2. Opposition to construction came from various citizens' groups and different levels of local government.
3. """Perfect Balance"" was produced and engineered by Lionel Hicks."
4. It provides people with structure and purpose and a sense of identity.
5. I learned this from the late Mr. W. Simpson.

Sources

Source	Sentences
wiki	1,537,302 (92.9%)
sentence-collector	61,569 (3.7%)
covost2-xx_en	28,881 (1.7%)
Other	26,425 (1.6%)

Text domains

Code	Domain	Clips	Speakers
general	General	677 (0.0%)	334 (0.3%)
agriculture_food	Agriculture and Food	169 (0.0%)	115 (0.1%)
automotive_transport	Automotive and Transport	8 (0.0%)	7 (0.0%)
finance	Finance	44 (0.0%)	33 (0.0%)
service_retail	Service and Retail	31 (0.0%)	24 (0.0%)
healthcare	Healthcare	26 (0.0%)	22 (0.0%)
history_law_government	History, Law and Government	126 (0.0%)	94 (0.1%)
media_entertainment	Media and Entertainment	118 (0.0%)	92 (0.1%)
nature_environment	Nature and Environment	64 (0.0%)	46 (0.0%)
news_current_affairs	News and Current Affairs	13 (0.0%)	13 (0.0%)
technology_robotics	Technology and Robotics	104 (0.0%)	75 (0.1%)
language_fundamentals	Language Fundamentals	11 (0.0%)	10 (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 user
• path - relative path of the audio file
• sentence - the sentence to be read aloud
• sentence_id - unique identifier for the sentence
• sentence_domain - domain classification(s) of the sentence
• 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 speaker[^1]
• gender - gender of the speaker[^1]
• accents - accents of the speaker[^1]
• variant - variant of the language[^1]
• locale - locale code of the language
• segment - if sentence belongs to a custom dataset segment, it will be listed here

[^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.

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

• Common Voice translators on Pontoon
• Common Voice Communities

Discussions

• Common Voice on Matrix
• Common Voice on Discourse
• Common Voice on Discord
• Common Voice on Telegram

Contribute

• Speak
• Write
• Listen
• Review

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.