@inproceedings{gumma-etal-2024-muntts,
title = "{M}un{TTS}: A Text-to-Speech System for {M}undari",
author = "Gumma, Varun and
Hada, Rishav and
Yadavalli, Aditya and
Gogoi, Pamir and
Mondal, Ishani and
Seshadri, Vivek and
Bali, Kalika",
editor = "Moeller, Sarah and
Agyapong, Godfred and
Arppe, Antti and
Chaudhary, Aditi and
Rijhwani, Shruti and
Cox, Christopher and
Henke, Ryan and
Palmer, Alexis and
Rosenblum, Daisy and
Schwartz, Lane",
booktitle = "Proceedings of the Seventh Workshop on the Use of Computational Methods in the Study of Endangered Languages",
month = mar,
year = "2024",
address = "St. Julians, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.computel-1.11",
pages = "76--82",
abstract = "We present MunTTS, an end-to-end text-to-speech (TTS) system specifically for Mundari, a low-resource Indian language of the Austo-Asiatic family. Our work addresses the gap in linguistic technology for underrepresented languages by collecting and processing data to build a speech synthesis system. We begin our study by gathering a substantial dataset of Mundari text and speech and train end-to-end speech models. We also delve into the methods used for training our models, ensuring they are efficient and effective despite the data constraints. We evaluate our system with native speakers and objective metrics, demonstrating its potential as a tool for preserving and promoting the Mundari language in the digital age.",
}
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%0 Conference Proceedings
%T MunTTS: A Text-to-Speech System for Mundari
%A Gumma, Varun
%A Hada, Rishav
%A Yadavalli, Aditya
%A Gogoi, Pamir
%A Mondal, Ishani
%A Seshadri, Vivek
%A Bali, Kalika
%Y Moeller, Sarah
%Y Agyapong, Godfred
%Y Arppe, Antti
%Y Chaudhary, Aditi
%Y Rijhwani, Shruti
%Y Cox, Christopher
%Y Henke, Ryan
%Y Palmer, Alexis
%Y Rosenblum, Daisy
%Y Schwartz, Lane
%S Proceedings of the Seventh Workshop on the Use of Computational Methods in the Study of Endangered Languages
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julians, Malta
%F gumma-etal-2024-muntts
%X We present MunTTS, an end-to-end text-to-speech (TTS) system specifically for Mundari, a low-resource Indian language of the Austo-Asiatic family. Our work addresses the gap in linguistic technology for underrepresented languages by collecting and processing data to build a speech synthesis system. We begin our study by gathering a substantial dataset of Mundari text and speech and train end-to-end speech models. We also delve into the methods used for training our models, ensuring they are efficient and effective despite the data constraints. We evaluate our system with native speakers and objective metrics, demonstrating its potential as a tool for preserving and promoting the Mundari language in the digital age.
%U https://aclanthology.org/2024.computel-1.11
%P 76-82
Markdown (Informal)
[MunTTS: A Text-to-Speech System for Mundari](https://aclanthology.org/2024.computel-1.11) (Gumma et al., ComputEL-WS 2024)
ACL
- Varun Gumma, Rishav Hada, Aditya Yadavalli, Pamir Gogoi, Ishani Mondal, Vivek Seshadri, and Kalika Bali. 2024. MunTTS: A Text-to-Speech System for Mundari. In Proceedings of the Seventh Workshop on the Use of Computational Methods in the Study of Endangered Languages, pages 76–82, St. Julians, Malta. Association for Computational Linguistics.