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Task: ASR
Release Date: 3/22/2026
Format: MP3
Size: 306.15 MB
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A collection of read speech recordings in Wakhi (Wakhi (Wuk̃hikwor)).
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.
wbl)This datasheet is for cv-corpus-25.0-2026-03-09 of the Mozilla Common Voice Scripted Speech dataset for Wakhi [Wakhi (Wuk̃hikwor) - wbl]. The dataset contains 8192 clips representing 15.36 hours of recorded speech (12.12 hours validated) from 14 speakers, recorded from a text corpus of 5,607 sentences.
Wakhi or Wakhani is indigenously termed as K̃hikwor (contraction of Wuk̃hikwor). It's an old eastern Iranian or Iranic language within the Pamiri branch. Though, diasporas also live in Russia and Turkey as well as in the European, American an Australian continents, the Wakhi (or K̃hikwor) language is spoken indigenously in Pakistan, China, Afghanistan, Tajikistan and Kirghizistan.
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 | 968 (11.8%) | 1 (7.1%) |
| female_feminine | Female, feminine | - | - |
| transgender | Transgender | - | - |
| non-binary | Non-binary | - | - |
| do_not_wish_to_say | Prefer not to say | - | - |
| - | Unspecified | 7,224 (88.2%) | 14 (100.0%) |
Gender declared: 968 of 8,192 clips (11.8%), 0 of 14 speakers (0.0%)
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 | 40 (0.5%) | 1 (7.1%) |
| twenties | Twenties | - | - |
| thirties | Thirties | 45 (0.5%) | 1 (7.1%) |
| fourties | Fourties | - | - |
| fifties | Fifties | 25 (0.3%) | 1 (7.1%) |
| sixties | Sixties | 983 (12.0%) | 2 (14.3%) |
| seventies | Seventies | 5,358 (65.4%) | 1 (7.1%) |
| eighties | Eighties | - | - |
| nineties | Nineties | - | - |
| - | Unspecified | 1,741 (21.3%) | 12 (85.7%) |
Age declared: 6,451 of 8,192 clips (78.7%), 2 of 14 speakers (14.3%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 6,464 (78.9%) |
| Invalidated | 89 (1.1%) |
| Other | 1,639 (20.0%) |
Training splits
| Split | Clips |
|---|---|
| Train | 2,542 (39.3%) |
| Dev | 1,110 (17.2%) |
| Test | 1,128 (17.5%) |
Training split coverage: 4,780 of 6,464 validated clips (73.9%)
The dataset contains 6464 validated, 89 invalidated, and 1639 unresolved clips. The average clip duration is 6.753 seconds.
The corpus has sentences of Hunza Wakhi and based on extensive anthropological and linguistic fieldwork in Pakistan, China, Afghanistan and Tajikistan.
Validated sentences: 5,493
| Category | Count |
|---|---|
| Unvalidated sentences | 114 |
| Pending sentences | 114 |
| Rejected sentences | - |
| Reported sentences | 1 |
The corpus contains 5,607 sentences: 5,493 validated and 114 unvalidated (114 pending review, 0 rejected), with 1 reported for review.
The script used is Roman Anglicized writing system, which is the approved script by Wakhi Tajik Cultural Association (WTCA), Pakistan, an Ishkoman Wakhi Welfare Organization (IWWO). Through this script, the literate Wakhi people easily and happily interact with each other across the borders on social media forums: it thus facilitates their creativities, thought expression in textual form and binds them together.
D̃d̃ Dh Ee Ẽẽ Ff Gg Gh g̃h Ii Jj J̃j̃ Kk Kh K̃h Ll Mm Nn Oo Pp Qq Rr Ss Sh S̃h Tt T̃t̃ Th Uu Ũũ Vv Ww Yy Zz Zh Z̃hZ̃z̃
There follows a randomly selected sample of five sentences from the corpus.
Yan yi gheyr mulkiyi bimor vitk.
Sake Kitob Joyetu
Wozi k̃hat: “Wuz beh nomardi taw neh yundem.”
Johil zẽmanẽs̃h dowlatẽt sũratẽ dẽstan k̃hũ tat nanẽ lecrẽn
Yan, dẽ yi khun ney dẽ yi khun yow goten.
Texts (sentences) made out of my own brain (creation) during the assignment period.
Texts out of selected Wakhi poetries.
New Wakhi transcriptions (texts) of the interviews out of my extensive fieldwork in Pakistan, china, Afghanistan and Tajikistan
Wakhi publications from formal website: www.fazalamin.com
| Source | Sentences |
|---|---|
| Self | 3,313 (60.3%) |
| self | 2,175 (39.6%) |
| Other | 5 (0.1%) |
General
| Code | Domain | Clips | Speakers |
|---|---|---|---|
| general | General | - | - |
| agriculture_food | Agriculture and Food | - | - |
| automotive_transport | Automotive and Transport | - | - |
| finance | Finance | - | - |
| service_retail | Service and Retail | - | - |
| healthcare | Healthcare | - | - |
| history_law_government | History, Law and Government | - | - |
| media_entertainment | Media and Entertainment | - | - |
| nature_environment | Nature and Environment | 3 (0.0%) | 1 (7.1%) |
| news_current_affairs | News and Current Affairs | - | - |
| technology_robotics | Technology and Robotics | - | - |
| language_fundamentals | Language Fundamentals | - | - |
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)
Mazdak Beg
Ahmad Jami Sakhi
Mr. Amanullah
Fazal Amin Beg
This dataset was partially funded by the Open Multilingual Speech Fund managed by Mozilla Common Voice.
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