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Release Date: 9/17/2026
Format: MP3
Size: 276.61 MB
A collection of read speech recordings in Pahari-Pothwari (Pahari-Pothwari).
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.
phr)This datasheet is for cv-corpus-27.0-2026-09-11 of the Mozilla Common Voice Scripted Speech dataset for Pahari-Pothwari [Pahari-Pothwari - phr]. The dataset contains 12825 clips representing 14.11 hours of recorded speech (13.97 hours validated) from 63 speakers, recorded from a text corpus of 2,077 sentences.
Pahari-Pothwari is a group of dialects spoken in the Pothohar Plateau of Punjab, Pakistan, and across the border in Azad Jammu and Kashmir (AJK). The name is a combination of two closely related dialect clusters: Pahari (literally "of the hills") and Pothwari (referring to the Pothohar region). Pahari-Pothwari belongs to the Indo-Aryan family of languages. It shares lexical and grammatical similarity with these languages.
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 | 3,836 (29.9%) | 5 (7.9%) |
| transgender | Transgender | - | - |
| non-binary | Non-binary | - | - |
| do_not_wish_to_say | Prefer not to say | - | - |
| - | Unspecified | 8,989 (70.1%) | 61 (96.8%) |
Gender declared: 3,836 of 12,825 clips (29.9%), 2 of 63 speakers (3.2%)
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 | - | - |
| twenties | Twenties | 6,653 (51.9%) | 10 (15.9%) |
| thirties | Thirties | 2,237 (17.4%) | 3 (4.8%) |
| fourties | Fourties | 195 (1.5%) | 1 (1.6%) |
| fifties | Fifties | - | - |
| sixties | Sixties | - | - |
| seventies | Seventies | - | - |
| eighties | Eighties | - | - |
| nineties | Nineties | - | - |
| - | Unspecified | 3,740 (29.2%) | 56 (88.9%) |
Age declared: 9,085 of 12,825 clips (70.8%), 7 of 63 speakers (11.1%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 12,695 (99.0%) |
| Invalidated | 120 (0.9%) |
| Other | 10 (0.1%) |
Training splits
| Split | Clips |
|---|---|
| Train | 743 (5.9%) |
| Dev | 673 (5.3%) |
| Test | 656 (5.2%) |
Training split coverage: 2,072 of 12,695 validated clips (16.3%)
The dataset contains 12695 validated, 120 invalidated, and 10 unresolved clips. The average clip duration is 3.963 seconds.
The dataset comprises a speech corpus totaling 15 hours, containing 2,077 Pahari sentences. The primary source for the corpus was the published books by Dr. Muhammad Saghir Khan, a distinguished literary figure and academician from Rawalakot, Poonch. This was supplemented with a smaller collection of sentences gathered from the daily conversations of native Pahari speakers. The entire set of written sentences was then recorded by 63 native speakers, all of whom are residents of the Poonch region of Azad Jammu and Kashmir.
Validated sentences: 2,077
| Category | Count |
|---|---|
| Unvalidated sentences | - |
| Pending sentences | - |
| Rejected sentences | - |
| Reported sentences | 1 |
The corpus contains 2,077 sentences: 2,077 validated and 0 unvalidated (0 pending review, 0 rejected), with 1 reported for review.
The writing system used for the corpus is based on the Urdu orthography. The corpus was written using the same Urdu script and follows the right-to-left direction of Urdu.
The Urdu alphabet was utilized for transcription.
There follows a randomly selected sample of five sentences from the corpus.
کھیل تماشیاں نی جاغ وی ہُن موبائلے نئیں گیمیں ملی شوڑی
سارے ہک دوئے کنے ملی جُلی رہنے
دس او کیاں آئے نے سے
مجید آخنے لاغیس، کم دس خان
نی بچہ، جیاں میں آخنی دیوس اویاں کر
Published books of Dr. Muhammad Saghir Khan. Daily conversation of Pahari speakers.
| Source | Sentences |
|---|---|
| ست برگے ناں پھُل | 1,153 (55.5%) |
| کھٹی بٹی | 557 (26.8%) |
| Self | 248 (11.9%) |
| مولاچھ | 74 (3.6%) |
| بنجاراں | 45 (2.2%) |
General
The text was written in Unicode, following the conventions of Urdu orthography.
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 speaker1
gender - gender of the speaker1
accents - accents of the speaker1
variant - variant of the language1
locale - locale code of the language
segment - if sentence belongs to a custom dataset segment, it will be listed here
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)
Dr. Muhammad Saghir Khan
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