HamaraAwaz: Advancing Low-Latency Streaming TTS for Multilingual Speech in Indian Languages
Neil Kumar Shah, Parth Khadse, Shirish S. Karande, Sunil Kumar Kopparapu
Abstract
We present a multilingual, multi-speaker, low-latency speech synthesis system developed by the HamaraAwaz team for Track 1 of the LIMMITS’25 challenge. To improve speaker similarity and naturalness in Indic languages, we build on ParrotTTS. We utilize disentangled self-supervised speech representations and incorporate enhancements such as Byte-Pair Encoding for text representation to reduce latency and relative positional representations to enhance speech quality. The proposed model achieved a naturalness Mean Opinion Score (MOS) of 3.51 and a speaker similarity score of 3.53 in the LIMMITS’25 grand challenge held as part of ICASSP-25. Speech samples are available at https://parrot-tts.github.io/HamaraAwaz/
BibTeX
@inproceedings{icassp2025_hamaraawazadvanc,
title = {HamaraAwaz: Advancing Low-Latency Streaming TTS for Multilingual Speech in Indian Languages},
author = {Neil Kumar Shah and Parth Khadse and Shirish S. Karande and Sunil Kumar Kopparapu},
booktitle = {ICASSP 2025},
year = {2025}
}