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Task: ASR
Release Date: 3/22/2026
Format: MP3
Size: 374.55 MB
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A collection of read speech recordings in Torwali (توروالی).
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.
trw)This datasheet is for cv-corpus-25.0-2026-03-09 of the Mozilla Common Voice Scripted Speech dataset for Torwali [توروالی - trw]. The dataset contains 12431 clips representing 18.55 hours of recorded speech (16.49 hours validated) from 27 speakers, recorded from a text corpus of 7,797 sentences.
Torwali is an Indo-Aryan language belongs to its sub-group Dardic and is spoken by about 150k people in the upper mountainous reaches of the Swat valley in Pakistan.
| Code | Accent | Clips | Speakers |
|---|---|---|---|
| - | 6,586 (53.0%) | 4 (14.8%) |
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 | - | - |
| female_feminine | Female, feminine | - | - |
| transgender | Transgender | - | - |
| non-binary | Non-binary | - | - |
| do_not_wish_to_say | Prefer not to say | - | - |
| - | Unspecified | 12,431 (100.0%) | 27 (100.0%) |
Gender declared: 0 of 12,431 clips (0.0%), 0 of 27 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 | 488 (3.9%) | 2 (7.4%) |
| twenties | Twenties | 4,234 (34.1%) | 7 (25.9%) |
| thirties | Thirties | 1,366 (11.0%) | 3 (11.1%) |
| fourties | Fourties | 4,492 (36.1%) | 4 (14.8%) |
| fifties | Fifties | 1,180 (9.5%) | 2 (7.4%) |
| sixties | Sixties | - | - |
| seventies | Seventies | - | - |
| eighties | Eighties | - | - |
| nineties | Nineties | - | - |
| - | Unspecified | 671 (5.4%) | 15 (55.6%) |
Age declared: 11,760 of 12,431 clips (94.6%), 12 of 27 speakers (44.4%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 11,054 (88.9%) |
| Invalidated | 1,363 (11.0%) |
| Other | 14 (0.1%) |
Training splits
| Split | Clips |
|---|---|
| Train | 2,859 (25.9%) |
| Dev | 2,083 (18.8%) |
| Test | 1,956 (17.7%) |
Training split coverage: 6,898 of 11,054 validated clips (62.4%)
The dataset contains 11054 validated, 1363 invalidated, and 14 unresolved clips. The average clip duration is 5.373 seconds.
There are more than 7000 sentences from various books produced in Torwali by the local indigenous organization Idara Baraye Taleem wa Taraqi (IBT) and its volunteers.
Validated sentences: 7,770
| Category | Count |
|---|---|
| Unvalidated sentences | 27 |
| Pending sentences | 20 |
| Rejected sentences | 7 |
| Reported sentences | 578 |
The corpus contains 7,797 sentences: 7,770 validated and 27 unvalidated (20 pending review, 7 rejected), with 578 reported for review.
The writing system is based on the Perso-Arabic script
أ ا اَ آ اِ اُ اُو او ای اے ب پ ت ٹ ث ج چ ڇ ح خ د ڈ ذ ر ڑ ژ ز ڙ س ش ݜ ص ض ط ظ ع غ ک گ ف ق ل م ن ں ہ ء ے ی بھ پھ تھ ٹھ جھ چھ ڇھ دھ ڈھ ڑھ ڙھ کھ گھ لھ مھ نھ
There follows a randomly selected sample of five sentences from the corpus.
بوپ دأدی جیِب سی بنیاد تے دأل جیبا می تعلیم سی منصوبا چھی۔
آ کم گے بیَدو
ملانگ کمیئی کمیئی بے ہُوش ہُوئی او بارام شاھزدا ایسی أنگی سارُو سأد۔
سے تعداد می تھلا کم آشی خو مُوٹھائے بیشتے گھین طاقت سوابش بھؤدُود
رینگی سالُو بنَدُو: ”تأ آج یِؤ سی غلطی کی! تُو ازر خطا ہُو۔“
Torwali-Urdu-English Dictionary by Idara Baraye Taleem wa Taraqi (IBT)
Torwali-English Dictionary for Students by Idara Baraye Taleem wa Taraqi (IBT)
Torwali Folktales by Idara Baraye Taleem wa Taraqi (IBT)
Torwali children’s books by Idara Baraye Taleem wa Taraqi (IBT)
Inaan 1 by Idara Baraye Taleem wa Taraqi (IBT)
Inaan 2 by Idara Baraye Taleem wa Taraqi (IBT)
Jinnah si Qisa by Idara Baraye Taleem wa Taraqi (IBT)
Fatima Jinnah si Qisa by Idara Baraye Taleem wa Taraqi (IBT)
Allama Iqbal si Qisia by Idara Baraye Taleem wa Taraqi (IBT)
Kashmala by Idara Baraye Taleem wa Taraqi (IBT)
Sultan Bahu Si Qisa by Idara Baraye Taleem wa Taraqi (IBT)
Surat-e-Rahman si Tarjuma by Idara Baraye Taleem wa Taraqi (IBT)
Akhrir Dash Surata- si An Nimaaz si Tarjuma by Idara Baraye Taleem wa Taraqi (IBT)
Poetry by Javid Iqbal Torwali ‘
Poetry by Zubair Torwali
Essays by Zubair Torwali
Essays by Aftab Ahmad
Essays by Nisar Ahmad Torwali
Essays by Rahim Sabir
Novel by Zubair Torwali
| Source | Sentences |
|---|---|
| self | 3,284 (42.5%) |
| Torwali English Dictionary for Students | 986 (12.8%) |
| Idara Baraye Taleem wa Taraqi (IBT), Jabvid Iqbal Torwali | 984 (12.7%) |
| Self | 621 (8.0%) |
| Pakistan Academy of Letters | 487 (6.3%) |
| Nisar Ahmad Torwali & Mahmood Torwali | 253 (3.3%) |
| Idara Baraye Taleem wa Taraqi (IBT), Javid Iqbal Torwali | 223 (2.9%) |
| "Sabir, Rahim (2017). ""Torwali Folktales"". Pakistan Academy of Letters, Islamabad Pakistan" | 215 (2.8%) |
| Idara Baraye Taleem wa Taraqi (BT) | 87 (1.1%) |
| Other | 590 (7.6%) |
General, Agriculture and Food, Automotive and Transport, Finance, Service and Retail, Healthcare, History, Law and Governmant, Media and Entertainment, Nature and Environment, News and Current Affairs, Technology and Robotics, Language Fundamentals (e.g. Digits, Letters, Money)
| Code | Domain | Clips | Speakers |
|---|---|---|---|
| general | General | 55 (0.4%) | 9 (33.3%) |
| agriculture_food | Agriculture and Food | 57 (0.5%) | 11 (40.7%) |
| automotive_transport | Automotive and Transport | 2 (0.0%) | 2 (7.4%) |
| finance | Finance | 2 (0.0%) | 2 (7.4%) |
| service_retail | Service and Retail | 57 (0.5%) | 11 (40.7%) |
| healthcare | Healthcare | 49 (0.4%) | 9 (33.3%) |
| history_law_government | History, Law and Government | 49 (0.4%) | 9 (33.3%) |
| media_entertainment | Media and Entertainment | 1 (0.0%) | 1 (3.7%) |
| nature_environment | Nature and Environment | 63 (0.5%) | 11 (40.7%) |
| news_current_affairs | News and Current Affairs | 67 (0.5%) | 12 (44.4%) |
| technology_robotics | Technology and Robotics | - | - |
| language_fundamentals | Language Fundamentals | 17 (0.1%) | 6 (22.2%) |
Audio recording of the text corpus
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)
Zubair Torwali
Javid Iqbal Torwali
Nisar Ahmad Torwali
Rahim Sabir
Aftab Ahmad
Sajad Ahmad
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