88 citations · 308 across the 88 of their papers we have counts for
6 papers · 1 filter
JSUT corpus: free large-scale Japanese speech corpus for end-to-end speech synthesis
Ryosuke Sonobe, Shinnosuke Takamichi, Hiroshi Saruwatari
Thanks to improvements in machine learning techniques including deep learning, a free large-scale speech corpus that can be shared between academic institutions and commercial comp…
Independent Low-Rank Matrix Analysis Based on Parametric Majorization-Equalization Algorithm
Yoshiki Mitsui, Daichi Kitamura, Norihiro Takamune +3
In this paper, we propose a new optimization method for independent low-rank matrix analysis (ILRMA) based on a parametric majorization-equalization algorithm. ILRMA is an efficien…
Statistical Parametric Speech Synthesis Incorporating Generative Adversarial Networks
Yuki Saito, Shinnosuke Takamichi, Hiroshi Saruwatari
A method for statistical parametric speech synthesis incorporating generative adversarial networks (GANs) is proposed. Although powerful deep neural networks (DNNs) techniques can…
Independent Low-Rank Matrix Analysis Based on Complex Student's -Distribution for Blind Audio Source Separation
Shinichi Mogami, Daichi Kitamura, Yoshiki Mitsui +3
In this paper, we generalize a source generative model in a state-of-the-art blind source separation (BSS), independent low-rank matrix analysis (ILRMA). ILRMA is a unified method…
Sampling-based speech parameter generation using moment-matching networks
Shinnosuke Takamichi, Tomoki Koriyama, Hiroshi Saruwatari
This paper presents sampling-based speech parameter generation using moment-matching networks for Deep Neural Network (DNN)-based speech synthesis. Although people never produce ex…
Voice Conversion Using Sequence-to-Sequence Learning of Context Posterior Probabilities
Hiroyuki Miyoshi, Yuki Saito, Shinnosuke Takamichi +1
Voice conversion (VC) using sequence-to-sequence learning of context posterior probabilities is proposed. Conventional VC using shared context posterior probabilities predicts targ…