Common Voice Scripted Speech 25.0 - Dameli

dml — Dameli (dml)

This datasheet is for cv-corpus-25.0-2026-03-09 of the Mozilla Common Voice Scripted Speech dataset for Dameli [dml - dml]. The dataset contains 6482 clips representing 10.83 hours of recorded speech (10.22 hours validated) from 5 speakers, recorded from a text corpus of 6,346 sentences.

Language

Dameli is one of the most vulnerable languages of Pakistan. The language is spoken in a few remote villages, Asper, Dondidari, Ponagram and Shintari and the surrounding hamlets in the side valley called Damel in northern mountainous area of district Chitral of Khyber Pakhtunkhwa province. This vulnerability becomes more critical because of the community’s fewer numbers of speakers (about 6500 in total) In UNESCO’S Atlas of the world languages in Danger, Dameli is listed as “Severely endangered” (Elnazarov, 2010).The entry on Dameli was contributed by Hakim Elnazarov, and was based on information in Decker (1992).

Demographic information

The dataset includes the following self-declared age and gender distributions. A coverage summary is shown below each table.

Gender

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.

Gender declared: 0 of 6,482 clips (0.0%), 0 of 5 speakers (0.0%)

Age

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.

Age declared: 5,969 of 6,482 clips (92.1%), 0 of 5 speakers (0.0%)

Data splits for modelling

Clip buckets

Training splits

Training split coverage: 4,917 of 6,115 validated clips (80.4%)

The dataset contains 6115 validated, 68 invalidated, and 299 unresolved clips. The average clip duration is 6.019 seconds.

Text corpus

The corpus consists of 5,670 sentences in the Dameli language. The data was collected from multiple sources, including published books in Dameli, community-written materials, and newly created sentences designed to reflect everyday use of the language. The aim of compiling this corpus is to represent a wide range of topics such as social life, education, agriculture, economy, poetry, farming, and history. This balanced collection provides a valuable resource for linguistic analysis, documentation, and language technology development.

Validated sentences: 5,670

The corpus contains 6,346 sentences: 5,670 validated and 676 unvalidated (676 pending review, 0 rejected), with 0 reported for review.

Writing system

The Dameli corpus is written using the Arabic script (Perso-Arabic style), which is commonly used for many regional languages in Pakistan. The writing system has been adapted to represent Dameli sounds, with some additional diacritics and letters used where necessary to capture specific phonetic distinctions.

Symbol table

آ ا ب پ ت ٹ ث ج چ ڇ څ ح خ د ڈ ذ ر ڑ ز ڙ ژ س ش ݜ ص ض ط ظ ع غ ف ق ک گ ل م ن ݨ و ہ ھ ء ی ے

Sample

There follows a randomly selected sample of five sentences from the corpus.

1. لاٹ کُری اینچ څِپی ماڜ لے زرائی تھے تنی

2. کُکُشہ پریویں کی منے بئی ہڈو نی آڅن بڜ

3. انار زادی تِھنا تے ورے ساں کَھل بئیں دڇِنُن

4. ایک ور خو خطائیہ تاں منے ایس تیر بن بڜ

5. تو پرَمُݜٹئں کی خوعصمت ساں برین گٹِنا

Sources

The text corpus was compiled from the following sources:

• Published books in the Dameli language

• Unpublished community manuscripts and notes

• Folk stories, oral traditions, and poetry transcribed into written form

• Newly created sentences for grammar and vocabulary coverage

• Educational and social materials produced by local speakers

Text domains

General, Agriculture and Food, Finance, Service and Retail, Healthcare, History, Law and Governmant, Media and Entertainment, Nature and Environment, Language Fundamentals (e.g. Digits, Letters, Money)

Processing

The collected texts were first gathered from books, manuscripts, and community contributions. Additional sentences were created to cover gaps in vocabulary and grammar. All materials were transcribed into a consistent format using the Arabic (Perso-Arabic) script adapted for Dameli. The data was then carefully reviewed and proofread to remove errors and ensure accuracy. Finally, the sentences were digitized, standardized, and compiled into a single corpus of 5,670 sentences for use in research and language development.

Recommended post-processing

Users of this dataset may consider the following post-processing steps depending on their research goals:

• Normalization: Ensure consistent spelling, especially where multiple variants of the same word exist.

• Tokenization: Segment the text into words or morphemes for computational use.

• POS tagging / annotation: Add part-of-speech or grammatical tags if the dataset will be used for linguistic or NLP applications.

• Transliteration: Convert the Arabic script into Latin script if required for cross-linguistic comparison.

• Alignment: If paired with translations, align Dameli sentences with their equivalents in other languages for bilingual analysis.

Fields

Clips

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.tsv

The 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.tsv

The 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)

Get involved

Community links

As internet access is limited in the Dameli Valley, most local communication takes place through community gatherings, cultural events, and village meeting. However, Dameli people living in cities and outside the valley stay connected online. They maintain a WhatsApp group called “Anjuman Taraqi Damyan Basha”, where members share poetry, cultural materials, news, and language-related resources. In this way, both offline and online platforms help keep the community connected and engaged in language preservation.

• Common Voice translators on Pontoon

• Common Voice Communities

Discussions

There are no formal online forums or blogs for discussions related to the dataset. Instead, most of the discussion and coordination took place in the WhatsApp group “Anjuman Taraqi Damyan Basha”, where community members exchanged ideas, shared poetry, cultural materials, and contributed to decisions during the dataset creation process.

• Common Voice on Matrix

• Common Voice on Discourse

• Common Voice on Discord

• Common Voice on Telegram

Contribute

• Speak

• Write

• Listen

• Review

Acknowledgements

Datasheet authors

Common Voice Community

Funding

This dataset was partially funded by the Open Multilingual Speech Fund managed by Mozilla Common Voice.

Licence

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.

Footnotes

1. 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