Scaling Nvidia’s Multi-Speaker Multi-Lingual TTS Systems With Zero-Shot TTS to Indic Languages-Reference-Cited by-同舟云学术

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Scaling Nvidia’s Multi-Speaker Multi-Lingual TTS Systems With Zero-Shot TTS to Indic Languages

Published:2024-04-14 Issue: Volume:33 Page:115-116
ISSN:
Container-title:2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)
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Author:

Arora Akshit¹,Badlani Rohan¹,Kim Sungwon¹,Valle Rafael¹,Catanzaro Bryan¹

Affiliation:

1. NVIDIA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10625769/10625780/10626687.pdf?arnumber=10626687

Reference6 articles.

1. RAD-MMM: Multilingual Multiaccented Multispeaker Text To Speech

2. P-flow: A fast and data-efficient zero-shot TTS through speech prompting;Kim

3. Hifi-gan: Generative adversarial networks for efficient and high fidelity speech synthesis;Kong

4. Vani: Very-Lightweight Accent-Controllable TTS for Native And Non-Native Speakers With Identity Preservation

5. LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech

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