VANI: Very-lightweight Accent-controllable TTS for Native and Non-native speakers with Identity Preservation
Badlani, Rohan, Arora, Akshit, Ghosh, Subhankar, Valle, Rafael, Shih, Kevin J., Santos, João Felipe, Ginsburg, Boris, Catanzaro, Bryan
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Mar-13-2023