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The Academia Sinica Systems of Voice Conversion for VCC2020

6 October 2020
Yu-Huai Peng
Cheng-Hung Hu
A. Kang
Hung-Shin Lee
Pin-Yuan Chen
Yu Tsao
Hsin-Min Wang
ArXiv (abs)PDFHTML
Abstract

This paper describes the Academia Sinica systems for the two tasks of Voice Conversion Challenge 2020, namely voice conversion within the same language (Task 1) and cross-lingual voice conversion (Task 2). For both tasks, we followed the cascaded ASR+TTS structure, using phonetic tokens as the TTS input instead of the text or characters. For Task 1, we used the international phonetic alphabet (IPA) as the input of the TTS model. For Task 2, we used unsupervised phonetic symbols extracted by the vector-quantized variational autoencoder (VQVAE). In the evaluation, the listening test showed that our systems performed well in the VCC2020 challenge.

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