About Kok Borok

Kok Borok (ISO 639-3: trp, Glottocode: kokb1239), also known as Kokborok or Tripuri, belongs to the Tibeto-Burman language family. Within this family, it is classified under the Bodo-Garo branch of the Sal subfamily. According to the Census of India 2011, there are approximately 1,011,294 speakers of "Tripuri" (which includes Kok Borok as the dominant variety) in India. The principal region of Kok Borok speakers is the state of Tripura in Northeast India, where it holds official status. Smaller communities of speakers are located in the neighbouring states of Assam and Mizoram, as well as in adjacent border areas of Bangladesh.

Dataset Description

The Kok Borok Speech Dataset, developed as part of the Speech Datasets and Models for Tibeto-Burman Languages (Project SpeeD-TB), funded under Mission Bhashini, is a transcribed speech corpus of the language. The full dataset comprises over 200 hours of high-quality audio recordings paired with accurate transcriptions in both IPA and Roman script, making it ** one of the largest speech resources for the language**, which not only enables building and evaluating voice models in low-resource linguistic settings but also enables large-scale linguistic description and documentation of the language. The audio data captures a diverse range of speakers across different age groups, genders, and education levels, ensuring variability in pronunciation, speech patterns, and tone. It includes both spontaneous and read speech collected in naturalistic and semi-controlled environments, thereby reflecting real-world linguistic usage. The transcriptions are carefully prepared and normalised to maintain consistency, supporting robust model training. This dataset also contributes to the preservation and digital documentation of the language and culture by transforming oral knowledge into structured, machine-readable formats.

Almost 60% of the data in the corpus is included from domains of agriculture, education and science & technology. The rest of the data is from varied domains including culture, lifecycle, sports, entertainment, healthcare and oral history, thereby giving extensive coverage. We have also used a variety of elicitation methods for collecting the data, including translations, narrations, lectures, role-play, spontaneous conversations, interviews and picture and video descriptions. The released dataset is meticulously mapped to rich metadata, including demographic and linguistic metadata of the speakers, domains, elicitation methods and individual prompts. The audio included in the current dataset is already sliced at sentence level, thereby ready to be integrated into the model training pipeline out-of-the-box.

The overall dataset of the project is collected over multiple phases and using multiple questionnaires. This repository contains the full dataset for the data collected from YouTube.

Ethical Considerations, IPR and Attribution

This repository represents our commitment to not only fair remuneration to the speakers of the language but also to co-ownership and equal IPR to all the contributors who have built the dataset. We believe this is the first step to move away from extractive data collection and use practices and ensure fairness in our treatment of the community members. As such, we have listed all speakers and transcribers as Contributors to the dataset. This dataset is only licensed to other researchers for use in their research projects. More details about licensing and commercial use conditions are given in the License and Commercial Use sections.

Direct relationships

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