activity
20182020
most citedVoice Transformer Network: Sequence-to-Sequence Voice Conversion Using Transformer with Text-to-Speech Pretraining

38 citations · 113 across the 10 of their papers we have counts for

collaborators

15 papers

eess.AS20207 cited

The Sequence-to-Sequence Baseline for the Voice Conversion Challenge 2020: Cascading ASR and TTS

Wen-Chin Huang, Tomoki Hayashi, Shinji Watanabe +1

This paper presents the sequence-to-sequence (seq2seq) baseline system for the voice conversion challenge (VCC) 2020. We consider a naive approach for voice conversion (VC), which…

eess.AS20202 cited

Predictions of Subjective Ratings and Spoofing Assessments of Voice Conversion Challenge 2020 Submissions

Rohan Kumar Das, Tomi Kinnunen, Wen-Chin Huang +5

The Voice Conversion Challenge 2020 is the third edition under its flagship that promotes intra-lingual semiparallel and cross-lingual voice conversion (VC). While the primary eval…

eess.AS202034 cited

Voice Conversion Challenge 2020: Intra-lingual semi-parallel and cross-lingual voice conversion

Yi Zhao, Wen-Chin Huang, Xiaohai Tian +5

The voice conversion challenge is a bi-annual scientific event held to compare and understand different voice conversion (VC) systems built on a common dataset. In 2020, we organiz…

eess.AS20203 cited

Pretraining Techniques for Sequence-to-Sequence Voice Conversion

Wen-Chin Huang, Tomoki Hayashi, Yi-Chiao Wu +2

Sequence-to-sequence (seq2seq) voice conversion (VC) models are attractive owing to their ability to convert prosody. Nonetheless, without sufficient data, seq2seq VC models can su…

eess.AS2020

A Cyclical Post-filtering Approach to Mismatch Refinement of Neural Vocoder for Text-to-speech Systems

Yi-Chiao Wu, Patrick Lumban Tobing, Kazuki Yasuhara +3

Recently, the effectiveness of text-to-speech (TTS) systems combined with neural vocoders to generate high-fidelity speech has been shown. However, collecting the required training…

eess.AS20202 cited

Quasi-Periodic Parallel WaveGAN Vocoder: A Non-autoregressive Pitch-dependent Dilated Convolution Model for Parametric Speech Generation

Yi-Chiao Wu, Tomoki Hayashi, Takuma Okamoto +2

In this paper, we propose a parallel WaveGAN (PWG)-like neural vocoder with a quasi-periodic (QP) architecture to improve the pitch controllability of PWG. PWG is a compact non-aut…