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VANI: Very-lightweight Accent-controllable TTS for Native and Non-native speakers with Identity Preservation (2303.07578v1)

Published 14 Mar 2023 in cs.SD, cs.LG, and eess.AS

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.

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Authors (8)
  1. Rohan Badlani (13 papers)
  2. Akshit Arora (2 papers)
  3. Subhankar Ghosh (41 papers)
  4. Rafael Valle (31 papers)
  5. Kevin J. Shih (18 papers)
  6. João Felipe Santos (7 papers)
  7. Boris Ginsburg (111 papers)
  8. Bryan Catanzaro (123 papers)
Citations (4)

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