Ryo Terashima — accepted AI-conference papers

2024

Enhancing Multilingual TTS with Voice Conversion Based Data Augmentation and Posterior Embedding

Hyun-Wook Yoon, Jin-Seob Kim, Ryuichi Yamamoto, Ryo Terashima, Chan-Ho Song, Jae-Min Kim +1

ICASSP 2024accepted

This paper proposes a multilingual, multi-speaker (MM) TTS system by using a voice conversion (VC)-based data augmentation method. Creating an MM-TTS model is challenging, owing to the difficulties of collecting polyglot data from multiple speakers. To address this problem, we adopt a cross-lingual,…

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2023

Period VITS: Variational Inference with Explicit Pitch Modeling for End-To-End Emotional Speech Synthesis

Yuma Shirahata, Ryuichi Yamamoto, Eunwoo Song, Ryo Terashima, Jae-Min Kim, Kentaro Tachibana

ICASSP 2023accepted

Several fully end-to-end text-to-speech (TTS) models have been proposed that have shown better performance compared to cascade models (i.e., training acoustic and vocoder models separately). However, they often generate unstable pitch contour with audible artifacts when the dataset contains emotiona…

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