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VANI: Very-lightweight Accent-controllable TTS for Native and Non-native speakers with Identity Preservation

Authors :
Badlani, Rohan
Arora, Akshit
Ghosh, Subhankar
Valle, Rafael
Shih, Kevin J.
Santos, João Felipe
Ginsburg, Boris
Catanzaro, Bryan
Publication Year :
2023

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 $F_0$ 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 $1$ and lightweight VANI model for Track $2$ and $3$ of the competition.<br />Comment: Presentation accepted at ICASSP 2023

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2303.07578
Document Type :
Working Paper