MunTTS: A Text-to-Speech System for Mundari
Gumma, Varun, Hada, Rishav, Yadavalli, Aditya, Gogoi, Pamir, Mondal, Ishani, Seshadri, Vivek, Bali, Kalika
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Jan-28-2024
- Country:
- Asia
- Europe
- France > Île-de-France
- Ireland > Leinster
- County Dublin > Dublin (0.04)
- North America > United States
- Maryland (0.04)
- Genre:
- Research Report (0.50)
- Industry:
- Information Technology (0.46)
- Technology:
- Information Technology > Artificial Intelligence
- Machine Learning > Neural Networks (0.94)
- Natural Language (1.00)
- Speech > Speech Synthesis (0.95)
- Vision > Optical Character Recognition (0.63)
- Information Technology > Artificial Intelligence