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Release Date: 9/17/2026
Format: MP3
Size: 1.33 GB
A collection of read speech recordings in Sindhi (Sindhi).
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.
sd)This datasheet is for cv-corpus-27.0-2026-09-11 of the Mozilla Common Voice Scripted Speech dataset for Sindhi [Sindhi - sd]. The dataset contains 66263 clips representing 73.38 hours of recorded speech (0.36 hours validated) from 35 speakers, recorded from a text corpus of 13,419 sentences.
Sindhi (سنڌي) is an Indo-Aryan language spoken mainly in Sindh, Pakistan, and also in India. It has millions of speakers, a rich literary history, and is written in both Perso-Arabic and Devanagari scripts.
| Code | Accent | Clips | Speakers |
|---|---|---|---|
| - | 10 (0.0%) | 2 (5.7%) |
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 | 13,040 (19.7%) | 2 (5.7%) |
| female_feminine | Female, feminine | - | - |
| transgender | Transgender | - | - |
| non-binary | Non-binary | - | - |
| do_not_wish_to_say | Prefer not to say | - | - |
| - | Unspecified | 53,223 (80.3%) | 34 (97.1%) |
Gender declared: 13,040 of 66,263 clips (19.7%), 1 of 35 speakers (2.9%)
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 | 26 (0.0%) | 2 (5.7%) |
| twenties | Twenties | 30 (0.0%) | 3 (8.6%) |
| thirties | Thirties | 15,759 (23.8%) | 2 (5.7%) |
| fourties | Fourties | 49,740 (75.1%) | 5 (14.3%) |
| fifties | Fifties | - | - |
| sixties | Sixties | - | - |
| seventies | Seventies | - | - |
| eighties | Eighties | - | - |
| nineties | Nineties | - | - |
| - | Unspecified | 708 (1.1%) | 30 (85.7%) |
Age declared: 65,555 of 66,263 clips (98.9%), 5 of 35 speakers (14.3%)
Clip buckets
| Bucket | Clips |
|---|---|
| Validated | 328 (0.5%) |
| Invalidated | 366 (0.6%) |
| Other | 65,569 (99.0%) |
Training splits
| Split | Clips |
|---|---|
| Train | 286 (87.2%) |
| Dev | - |
| Test | 42 (12.8%) |
Training split coverage: 328 of 328 validated clips (100.0%)
The dataset contains 328 validated, 366 invalidated, and 65569 unresolved clips. The average clip duration is 3.987 seconds.
The Sindhi corpus consists of collected texts from newspapers, and social media. It contains more then one lacs sentences. The texts cover different domains, including literature, news, education, and everyday communication.
Validated sentences: 13,348
| Category | Count |
|---|---|
| Unvalidated sentences | 71 |
| Pending sentences | 69 |
| Rejected sentences | 2 |
| Reported sentences | 10 |
The corpus contains 13,419 sentences: 13,348 validated and 71 unvalidated (69 pending review, 2 rejected), with 10 reported for review.
The Sindhi corpus is written in the Perso-Arabic script, which is the standard script used by Sindhi newspapers in Pakistan. It includes additional letters that represent Sindhi-specific sounds not found in standard Arabic.
The Sindhi Perso-Arabic script (used in newspapers) has 52 letters. Here is the full alphabet list separated by spaces:
ا ب ٻ ڀ پ ت ٿ ٽ ٺ ث ج جه ڄ چ ڇ ح خ د ڌ ڏ ڊ ڍ ذ ر ڙ ڍ ز س ش ص ض ط ظ ع غ ف ڦ ق ڪ گ ڳ گه ڱ ل ڻ ن ڃ م و ء ه ة ي ئ
There follows a randomly selected sample of five sentences from the corpus.
غالباً ان کي ”علم الاسماء“ چيو ويندو آهي، خبر ناهي ته هو ڪيترو ماهر هو.
اها قوت انسان کي برائي تي چڱائيءَ تي قائم رکڻ ۾ مدد ڪري ٿي
سو فقط آخرت لاءِ.
منهنجون خاموشيون ڏڪي رهيون آهن
في الحال، حڪومت اهڙين داخلا لاء ڪجھ به چارج نٿو ڪري
| Source | Sentences |
|---|---|
| Asad Memon (self) | 13,271 (99.4%) |
| Other | 77 (0.6%) |
General, Media and Entertainment, News and Current Affairs
| Code | Domain | Clips | Speakers |
|---|---|---|---|
| general | General | 169 (0.3%) | 6 (17.1%) |
| 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 | - | - |
| news_current_affairs | News and Current Affairs | - | - |
| technology_robotics | Technology and Robotics | - | - |
| language_fundamentals | Language Fundamentals | 5 (0.0%) | 5 (14.3%) |
The corpus was created by collecting texts from different Sindhi newspapers. The articles were gathered, cleaned to remove formatting issues, and then organized into a structured dataset for analysis.
It is recommended to clean the text for duplicate articles, normalize spellings, and remove unwanted symbols or formatting. Tokenization and sentence segmentation may also be useful for better analysis.
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)
Common Voice Community
This dataset was created with funding support from Mozilla. Special acknowledgments to Meesam Alam ([email protected]) for contributions and support.
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