MunTTS: A Text-to-Speech System for Mundari

Varun Gumma, Rishav Hada, Aditya Yadavalli, Pamir Gogoi, Ishani Mondal +2 more
1/28/2024
cs.CLcs.SDeess.AS

No official code found. Best implementation: microsoft/MunTTS-A-Text-to-Speech-System-For-Mundari (8 stars, MIT, last commit 2024-05-24).

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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Code Implementations(1)

microsoft/MunTTS-A-Text-to-Speech-System-For-MundariCommunity60%
MIT

Official Codebase for "MunTTS: A Text-to-Speech System for Mundari" (published in ComputEL-7)

80Shell, PythonMar 28, 20242 years agoMIT
low-resourcetext-to-speech

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Cite this paper

@article{gumma2024muntts,
  title  = {MunTTS: A Text-to-Speech System for Mundari},
  author = {Varun Gumma and Rishav Hada and Aditya Yadavalli and Pamir Gogoi and Ishani Mondal and Vivek Seshadri and Kalika Bali},
  year   = {2024},
  eprint = {2401.15579},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2401.15579v1}
}

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