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Release Date: 9/17/2026
Format: MP3
Size: 2.79 GB
A collection of read speech recordings in Turkish (Türkçe).
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.
tr)This datasheet is for cv-corpus-27.0-2026-09-11 of the Mozilla Common Voice Scripted Speech dataset for Turkish [Türkçe - tr]. The dataset contains 126794 clips representing 135.77 hours of recorded speech (130.22 hours validated) from 1840 speakers, recorded from a text corpus of 413,922 sentences.
Turkish is the most widely spoken language among Turkic languages and has around 100 million L1 speakers, which makes it the 18th most spoken language. It is the national language of Turkey and one of two official languages of Cyprus, and secondary languages of some neighboring countries. Many smaller groups in other countries exist, through migrations or communities from Ottoman era. These smaller groups should usually be categorized as a variant.
There are currently no variants defined for Common Voice Turkish dataset. It is worth noting that, until now, this dataset focused on literary Turkish, often called "Turkish of Turkey". There are also some L2 voices, mostly from immigrants coming into the country, but these can be categorized as "foreign accents".
| Code | Accent | Clips | Speakers |
|---|---|---|---|
| - | 49,330 (38.9%) | 162 (8.8%) |
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 | 53,420 (42.1%) | 460 (25.0%) |
| female_feminine | Female, feminine | 40,592 (32.0%) | 102 (5.5%) |
| transgender | Transgender | - | - |
| non-binary | Non-binary | - | - |
| do_not_wish_to_say | Prefer not to say | - | - |
| - | Unspecified | 32,782 (25.9%) | 1,392 (75.7%) |
Gender declared: 94,012 of 126,794 clips (74.1%), 448 of 1,840 speakers (24.3%)
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 | 1,957 (1.5%) | 55 (3.0%) |
| twenties | Twenties | 28,711 (22.6%) | 303 (16.5%) |
| thirties | Thirties | 10,839 (8.5%) | 163 (8.9%) |
| fourties | Fourties | 3,229 (2.5%) | 60 (3.3%) |
| fifties | Fifties | 8,940 (7.1%) | 30 (1.6%) |
| sixties | Sixties | 25,334 (20.0%) | 12 (0.7%) |
| seventies | Seventies | 4,187 (3.3%) | 2 (0.1%) |
| eighties | Eighties | 12,300 (9.7%) | 2 (0.1%) |
| nineties | Nineties | - | - |
| - | Unspecified | 31,297 (24.7%) | 1,346 (73.2%) |
Age declared: 95,497 of 126,794 clips (75.3%), 494 of 1,840 speakers (26.8%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 121,612 (95.9%) |
| Invalidated | 5,061 (4.0%) |
| Other | 121 (0.1%) |
Training splits
| Split | Clips |
|---|---|
| Train | 41,465 (34.1%) |
| Dev | 11,864 (9.8%) |
| Test | 11,874 (9.8%) |
Training split coverage: 65,203 of 121,612 validated clips (53.6%)
The dataset contains 121612 validated, 5061 invalidated, and 121 unresolved clips. The average clip duration is 3.855 seconds.
Actual values of text corpus from the previous version (please check the text corpus tab) show that:
Characters/Sentence of the whole corpus is 62.25, but validated set average is 35.915. Median values are 61 and 27 respectively.Words/Sentence of the whole corpus is 8.379, but validated set average is 5.096. Median values are 8 and 4 respectively.3.8 seconds on the average (in the previous dataset).
This value is increasing with each version, and we aim to reach 5 sec, which is the ideal minimum of most SotA model architectures.Validated sentences: 410,411
| Category | Count |
|---|---|
| Unvalidated sentences | 3,511 |
| Pending sentences | 59 |
| Rejected sentences | 3,452 |
| Reported sentences | 492 |
The corpus contains 413,922 sentences: 410,411 validated and 3,511 unvalidated (59 pending review, 3,452 rejected), with 492 reported for review.
Turkish uses an extended Latin alphabet.
Official Alphabet:
a b c ç d e f g ğ h ı i j k l m n o ö p r s ş t u ü v y zA B C Ç D E F G Ğ H I İ J K L M N O Ö P R S Ş T U Ü V Y ZAuxilary Characters (Arabic/Farsi loanwords): â î û Â Î Û
There follows a randomly selected sample of five sentences from the corpus.
The whole history of the text-corpora added throughout the years can be found in this forum post (Turkish). They mainly consist of:
Please note that:
| Source | Sentences |
|---|---|
| https://tr.wikipedia.org | 348,494 (85.0%) |
| sentence-collector | 47,746 (11.6%) |
| setimes | 5,077 (1.2%) |
| Other | 8,834 (2.2%) |
Until this version, we did not work on specialized sentence domains, except entries coming from individuals and ~300 numbers we added.
| Code | Domain | Clips | Speakers |
|---|---|---|---|
| general | General | 2 (0.0%) | 2 (0.1%) |
| agriculture_food | Agriculture and Food | - | - |
| automotive_transport | Automotive and Transport | 1 (0.0%) | 1 (0.1%) |
| finance | Finance | - | - |
| service_retail | Service and Retail | - | - |
| healthcare | Healthcare | - | - |
| history_law_government | History, Law and Government | - | - |
| media_entertainment | Media and Entertainment | 1 (0.0%) | 1 (0.1%) |
| nature_environment | Nature and Environment | - | - |
| news_current_affairs | News and Current Affairs | - | - |
| technology_robotics | Technology and Robotics | - | - |
| language_fundamentals | Language Fundamentals | 12 (0.0%) | 4 (0.2%) |
Except entries coming from individuals, we followed the following procedure for bulk additions to the text-corpus:
Please note that Turkish in Common Voice does not have a special language based validator, it uses the defaults.
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 filesentence - the sentence to be read aloudsentence_id - unique identifier for the sentencesentence_domain - domain classification(s) of the sentenceup_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 language1locale - locale code of the languagesegment - if sentence belongs to a custom dataset segment, it will be listed herevalidated_sentences.tsvThe 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 sentenceunvalidated_sentences.tsvThe 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 (pending or rejected)Main Channels:
Social media channels used during campaigns:
Most info can be found in Turkish language in the Discourse Turkish sub-forum. Other discussions are in Discourse main forum in English. Current discussions are on the Telegram group.
"How to contribute?", "What to avoid?", and similar topics for the newcomers can be found in the following forum post in Turkish: The process, rights & wrongs and dataset improvement
If you want to contribute, please first join the Telegram group.
Our future plans include:
You can find more information about how to participate in the Common Voice Project on the following page:
Community Participation Guidelines
Bülent Özden
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