VANI: Very-lightweight Accent-controllable TTS for Native and Non-native speakers with Identity Preservation
Sound
2023-03-15 v1 Machine Learning
Audio and Speech Processing
Abstract
We introduce VANI, a very lightweight multi-lingual accent controllable speech synthesis system. Our model builds upon disentanglement strategies proposed in RADMMM and supports explicit control of accent, language, speaker and fine-grained and energy features for speech synthesis. We utilize the Indic languages dataset, released for LIMMITS 2023 as part of ICASSP Signal Processing Grand Challenge, to synthesize speech in 3 different languages. Our model supports transferring the language of a speaker while retaining their voice and the native accent of the target language. We utilize the large-parameter RADMMM model for Track and lightweight VANI model for Track and of the competition.
Keywords
Cite
@article{arxiv.2303.07578,
title = {VANI: Very-lightweight Accent-controllable TTS for Native and Non-native speakers with Identity Preservation},
author = {Rohan Badlani and Akshit Arora and Subhankar Ghosh and Rafael Valle and Kevin J. Shih and João Felipe Santos and Boris Ginsburg and Bryan Catanzaro},
journal= {arXiv preprint arXiv:2303.07578},
year = {2023}
}
Comments
Presentation accepted at ICASSP 2023