Toto is an under-resourced and critically endangered Tibeto-Burman language spoken by a small community in Totopara village, Alipurduar district, West Bengal, India, with less than 1,000 speakers (and significantly lesser number of people proficient in the language). The language belongs to Dhimalish group of languages and is closely related to Dhimal, another language spoken in Northern West Bengal.

Dataset Description

The Toto 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 Toto,. The full dataset comprises over 200 hours of high-quality audio recordings paired with accurate transcriptions in both IPA and Bengali script, making it the first and largest 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 Toto language 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.

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

Abhit Toto, Ajita Toto, Amisha Toto , Anima Toto, Anita Toto, Anjana Toto, Anju Toto, Anuta toto, Aruna toto, Ashis toto, Bakul Toto, Baljit Toto , Bharat Toto, Bheltu Toto, Binod Toto, Binu Toto, Chumi Toto, Dalim Toto, Depoasmita toto, Dibya Toto, Dilip Toto, Gaurav Toto, Isuley Toto, Jolen Toto, Joy toto, Kajol Toto, Kiran Toto, Kiuti Toto, Kritan toto , Litchi Toto, Madina toto, Malay Toto, Manisha Toto, Mercy Toto, Mili Toto, Monojit Toto, Motiraj Toto, Nila Toto, Nilima Toto, Nimonjit Toto, Nirjala toto, Nirupa Toto, Nisha Toto, Nishul Toto, Pasang Toto, RAHUL TOTO, Rajia Toto, Rajit Toto, Rajiv toto, Rakhina Toto, Ramit Toto, Ramit toto, Renuka Toto, Rima Toto, Rimee Toto , Rimi Toto, Robin Toto, Rohit toto, Rokhina toto , Romin Toto, Ruma Toto, Runia Toto, SUNIT TOTO, Sadhona Toto, Sagar Toto, Sagar Toto , Sajid Toto, Sanchita Toto, Sanjay Toto, Sarajit Toto , Saranjit Toto, Sarojit Toto, Seema Toto, Shanti Toto, Shuvadip Toto, Shyam Toto, Sima Toto, Sobena Toto, Sonia Toto, Sova Toto , Subbi Toto, Surjana Toto, Surjana toto, Sushita Toto, Sushma Toto, Swapan Toto, Thupden Toto, babina toto, bibojit toto, budini Toto, getey toto, guduni toto, juna toto, kajal toto, khusboo toto, mangali toto, monojit toto, priya toto, probin Toto , resal toto, sahil toto, sanchita toto, sashita toto , shanti Toto, shiva toto, soniya toto, sujit Toto, sushma toto

Annotators

Adrita Bhattacharya, AnaghaS, Aniket Srivastava, Anindita, AnishaDutta, Arjunnaikguguloth, Ashistoto, Ishita Chowdhury, ManashiM, Shanti Toto, ShantiToto, SpeeD-TB Project, shyam

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.

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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