The Nyishi 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 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 ** 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 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 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. 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 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 in the field using structured and semi-structured interviews and spontaneous conversation.

About

Speedtb Phase 1 Nyishi Field Data

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.

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.

Tools

We employed Karya and Atekho for collecting and recording data. The complete dataset is transcribed and exported using MATra Lab. Both Atekho and MAtra Lab are part of the LiFE Suite Ecosystem, developed by Unreal Tece LLP.

Speakers

Aiya Gollom, Aiya gollom, Baby Mugli , Bagjam Ana, Bagjam ana, Bat Yagar, Bengia Ania, Biri Yachu , Byabang Chingsu, Byabang Sime, Byabang Yamin , Byabang sime , Chikhi Ahsu, Choho Rin, Churu Aka, DOBIAM TAKA, DUI TAKA, Daming Tadak, Deadpool, Dobiam Aniya, Dobiam Taka , Dobiem Yel, Dohu Kama, Dorai Eje, Gillo, Gollom Sime, Golo Palo, Gugnia Sime, Hinium Mama, Honi Japan, Ichiko Pito, Joram Aina and Joram Dui, Joram Aku, Joram Aruna, Joram Ayu, Joram Bida, Joram Byani, Joram Chobin, Joram I, Joram Jyoti, Joram Kimin, Joram Koda, Joram Maka, Joram Maloti, Joram Mama, Joram Maya, Joram Minu, Joram Motu, Joram Nama and Nabam Runaya, Joram Nikam , Joram Nikam and Joram Chobin, Joram Nina, Joram Niya, Joram Obbi, Joram Paul and Joram Yama, Joram Pera, Joram Puj, Joram Pumin, Joram Tacho, Joram Tachu, Joram Tahe, Joram Taja, Joram Taje, Joram Takap, Joram Tami, Joram Tane, Joram Tangam, Joram Tapu, Joram Tuka, Joram Yami, Joram Yaming, Joram Yano, Joram Yapa, Joram Yath, Joram Yaya, LIKHA BAI, Licha Ribia, Likh Ado, Likha Aku, Likha Ana , Likha Mama, Likha Mampi, Likha Ramleo, Likha Rich, Likha Taka, Likha Tana, Likha Tani, Likha Ya Joram, Likha Yami, Likha Yaze, Likha Yeli, Likka Aku, Lishi Aku, Lishi Taza Joram, Liydia, Locha Rozo, Meko Singhi, Mina Nihnaka, NABAM KHANDU, Nabam Jakap, Nabam Tara, Nangram Tare, Neelam Jeel, Neelam Joshua , Neelam Tolu, Neelam tolu, Nick Yano, Nikh Tado, Onum Churu, Pachurinya, Pel Kamin, Pochu, Pochu Mangu, Shri Joram Taja, Taba Torum, Taba Yopu, Taba_tato, Tabing Tatum, Tagan Mage, Taho Taku, Taj Jarbo, Taj Jikare, Taj Pera, Taj Rasap, Taj Takam, Taj Tatam, Taj Tating, Talo Martha, Talo Paga , TaloMartha, Talomary, Tania Tayer , Tar Ado, Tar Yakia, Tarak Tatam, Tare Yaya, Taw Sania, Techi Kujma, Techi mary, Togo Takap, Toko Doni, Toko Ipa, Toko Laam, Toko Rina, Toko Tali, Toko Yaram, Toko Yath, Toko Yaya, Toko rina, Totosuka, Yaming Sime, Yana Banang, Yowa Yapin, biki sima, byabang chingsu , donu kama, honi japan, joram paul, jorambell , lod yayo , pachu mello, phil tedi, phill doni, taho taku, talo badal, tame , toko laam, toko lel, uku toko, yowa Yapin

Annotators

Adrita Bhattacharya, Ahana Pramanik, AnaghaS, Anindita, Anisha Dutta, AnishaDutta, Ishita Chowdhury, Kanchan Potdar, Lishi Aku, ManashiM, SpeeD-TB Project

Structure

The dataset is organized by splits (e.g. train, test, validation).

Each row contains audio, audio-level metadata, prompt metadata and speaker metadata as described below:

Audio and Audio-level Metadata

audio: The audio file path (loaded as Audio feature in HF Datasets)
audio_id: Unique identifier for the audio
filename: Original filename
sentence-<SCRIPT>-transcription: Text transcription of the audio in the given script
speaker_id: Identifier for the speaker
boundaryID: Identifier for the boundary
start_time: Start time of the segment in seconds
end_time: End time of the segment in seconds

Prompt Metadata

'Q_Id`: Unique identifier for the question or prompt associated with the audio (maps to the question in the LiFE Questionnaire projects and accessible through the questionnaire repo)
'Domain': Domain of the audio (e.g., Agriculture, Education, General, etc.)
'Elicitation_Method`: Method used to elicit the speech (e.g., Translation, Narration, etc.)
Target: An optional field for translation indicating the grammatical structure being targeted for elicitation using the sentence.

Speaker Metadata

ageGroup: Age group of the speaker (e.g., 18-30, 30-50, etc.)
gender: Gender of the speaker
educationLevel: Education level of the speaker
educationMediumUpto12-list: Medium of education up to 12th grade (list of comma-separated values)
'educationMediumAfter12-list`: Medium of education after 12th grade (list of comma-separated values)
otherLanguages-list: Languages spoken by the speaker (list of comma-separated values) - this usually excludes the primary language of the dataset and is used to capture multilingualism in speakers.
nativeLanguage: The native language of the speaker (optional field if data is collected from non-native speakers of the language)
placeOfRecording: The location where the audio was recorded (optional field) or the native place of the speaker (if known)
typeOfplace: Whether the placeOfRecording mentioned is City, Town or Village.

Additional Metadata

textgrid_json: TextGrid data converted to JSON format In addition to any other metadata fields provided during upload are optionally included.

Dataset Explorer

The dataset could be explored on LiFE Suite by visiting the project public page.

License

This work is licensed under a CC-By-NC-SA-4.0 license. This license allows reusers to distribute, remix, adapt, build upon, and incorporate into software systems, the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. If you remix, adapt, build upon, or incorporate into software systems, you must license the modified material, including material generated by the software system, under identical terms, and license the software system under the GNU General Public License.

Commercial Use

If you are interested in using this dataset for commercial purposes, please contact us (contact [at] unreal-tece[dot]co[dot]in). Profits from commercial licensing will be distributed as royalties to the community members who contributed to this dataset.

Contact

For questions, issues, or contributions, open an issue on the dataset repository or contact us directly (contact [at] unreal-tece[dot]co[dot]in).

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