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20162024
most citedVoice Conversion from Unaligned Corpora using Variational Autoencoding Wasserstein Generative Adversarial Networks

151 citations · 423 across the 32 of their papers we have counts for

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Showing 2020Show all

8 papers · 1 filter

eess.AS2020★ 1 cited

Any-to-One Sequence-to-Sequence Voice Conversion using Self-Supervised Discrete Speech Representations

Wen-Chin Huang, Yi-Chiao Wu, Tomoki Hayashi +1

We present a novel approach to any-to-one (A2O) voice conversion (VC) in a sequence-to-sequence (seq2seq) framework. A2O VC aims to convert any speaker, including those unseen duri…

eess.AS2020★ 1 cited

The NU Voice Conversion System for the Voice Conversion Challenge 2020: On the Effectiveness of Sequence-to-sequence Models and Autoregressive Neural Vocoders

Wen-Chin Huang, Patrick Lumban Tobing, Yi-Chiao Wu +2

In this paper, we present the voice conversion (VC) systems developed at Nagoya University (NU) for the Voice Conversion Challenge 2020 (VCC2020). We aim to determine the effective…

cs.SD2020

Baseline System of Voice Conversion Challenge 2020 with Cyclic Variational Autoencoder and Parallel WaveGAN

Patrick Lumban Tobing, Yi-Chiao Wu, Tomoki Toda

In this paper, we present a description of the baseline system of Voice Conversion Challenge (VCC) 2020 with a cyclic variational autoencoder (CycleVAE) and Parallel WaveGAN (PWG),…

eess.AS2020★ 3 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★ 24 cited

Quasi-Periodic Parallel WaveGAN: A Non-autoregressive Raw Waveform Generative Model with Pitch-dependent Dilated Convolution Neural Network

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

In this paper, we propose a quasi-periodic parallel WaveGAN (QPPWG) waveform generative model, which applies a quasi-periodic (QP) structure to a parallel WaveGAN (PWG) model using…

eess.AS2020★ 29 cited

Quasi-Periodic WaveNet: An Autoregressive Raw Waveform Generative Model with Pitch-dependent Dilated Convolution Neural Network

Yi-Chiao Wu, Tomoki Hayashi, Patrick Lumban Tobing +2

In this paper, a pitch-adaptive waveform generative model named Quasi-Periodic WaveNet (QPNet) is proposed to improve the limited pitch controllability of vanilla WaveNet (WN) usin…

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.AS2020★ 2 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…