SpeeD-TB

## About Nyishi Nyishi is an under-resourced Tibeto-Burman language spoken by the Nyishi people, the largest ethnic group in Arunachal Pradesh, India. According to Census 2011, there are approximately **3 lakh speakers** of the languages. The language belongs to the Tani branch of the Tibeto-Burman language family. Owing to its status as one of the largest languages of Arunachal Pradesh, some resources for the language development such as corpus and a language model have been developed. However, the language lacks any large significant speech or text corpus. ## Dataset Description The Nyishi Speech Dataset, developed as part of the [Speech Datasets and Models for Tibeto-Burman Languages (Project SpeeD-TB)](https://sites.google.com/view/speed-tb/ "SpeeD-TB Project Website") funded under Mission Bhashini, is a transcribed speech corpus of Nyishi,. The full dataset comprises over **200 hours of high-quality audio recordings paired with accurate transcriptions in both IPA and Roman script**, making it the **the largest speech resource for the language** that 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, 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 Nyishi 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. Rest of the data is from varied domains including culture, lifecycle, sports, entertainment, healthcare and oral history, thereby, giving a large 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 a rich metadats including demographic and linguistic metadata of the speakers, domains, elicitation methods and to 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 language collected till now. ## Ethical Considerations, IPR and Attribution This repository represents our committment 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 the 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 (we insist that they are co-owners of the dataset even though HuggingFace does not provide us an explicit way of stating that) and they are further recognised as Speakers and Annotators of 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 License and Commercial Use sections.