29 citations · 84 across the 16 of their papers we have counts for
11 papers · 1 filter
Advancing Electrolaryngeal Speech Enhancement Through Speech-Text Representation Learning
Ding Ma, Jinyi Mi, Fengji Li +5
Objective: laryngectomees depend on an electromechanical device to generate electrolaryngeal (EL) speech. Compared with normal speech, EL speech suffers from severe distortion, lim…
crank: An Open-Source Software for Nonparallel Voice Conversion Based on Vector-Quantized Variational Autoencoder
Kazuhiro Kobayashi, Wen-Chin Huang, Yi-Chiao Wu +3
In this paper, we present an open-source software for developing a nonparallel voice conversion (VC) system named crank. Although we have released an open-source VC software based…
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…
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…
Generalization of Spectrum Differential based Direct Waveform Modification for Voice Conversion
Wen-Chin Huang, Yi-Chiao Wu, Kazuhiro Kobayashi +6
We present a modification to the spectrum differential based direct waveform modification for voice conversion (DIFFVC) so that it can be directly applied as a waveform generation…
Non-Parallel Voice Conversion with Cyclic Variational Autoencoder
Patrick Lumban Tobing, Yi-Chiao Wu, Tomoki Hayashi +2
In this paper, we present a novel technique for a non-parallel voice conversion (VC) with the use of cyclic variational autoencoder (CycleVAE)-based spectral modeling. In a variati…
Statistical Voice Conversion with Quasi-Periodic WaveNet Vocoder
Yi-Chiao Wu, Patrick Lumban Tobing, Tomoki Hayashi +2
In this paper, we investigate the effectiveness of a quasi-periodic WaveNet (QPNet) vocoder combined with a statistical spectral conversion technique for a voice conversion task. T…
Quasi-Periodic WaveNet Vocoder: A Pitch Dependent Dilated Convolution Model for Parametric Speech Generation
Yi-Chiao Wu, Tomoki Hayashi, Patrick Lumban Tobing +2
In this paper, we propose a quasi-periodic neural network (QPNet) vocoder with a novel network architecture named pitch-dependent dilated convolution (PDCNN) to improve the pitch c…
Investigation of F0 conditioning and Fully Convolutional Networks in Variational Autoencoder based Voice Conversion
Wen-Chin Huang, Yi-Chiao Wu, Chen-Chou Lo +6
In this work, we investigate the effectiveness of two techniques for improving variational autoencoder (VAE) based voice conversion (VC). First, we reconsider the relationship betw…
Refined WaveNet Vocoder for Variational Autoencoder Based Voice Conversion
Wen-Chin Huang, Yi-Chiao Wu, Hsin-Te Hwang +6
This paper presents a refinement framework of WaveNet vocoders for variational autoencoder (VAE) based voice conversion (VC), which reduces the quality distortion caused by the mis…
Collapsed speech segment detection and suppression for WaveNet vocoder
Yi-Chiao Wu, Kazuhiro Kobayashi, Tomoki Hayashi +2
In this paper, we propose a technique to alleviate the quality degradation caused by collapsed speech segments sometimes generated by the WaveNet vocoder. The effectiveness of the…