Search Results for author: Hiroshi Saruwatari

Found 19 papers, 2 papers with code

Low-Latency Incremental Text-to-Speech Synthesis with Distilled Context Prediction Network

no code implementations22 Sep 2021 Takaaki Saeki, Shinnosuke Takamichi, Hiroshi Saruwatari

Although this method achieves comparable speech quality to that of a method that waits for the future context, it entails a huge amount of processing for sampling from the language model at each time step.

Knowledge Distillation Language Modelling +3

Binaural rendering from microphone array signals of arbitrary geometry

no code implementations15 Sep 2021 Naoto Iijima, Shoichi Koyama, Hiroshi Saruwatari

To reproduce binaural signals from microphone array recordings at a remote location, a spherical microphone array is generally used for capturing a soundfield.

Sampling-Frequency-Independent Audio Source Separation Using Convolution Layer Based on Impulse Invariant Method

no code implementations10 May 2021 Koichi Saito, Tomohiko Nakamura, Kohei Yatabe, Yuma Koizumi, Hiroshi Saruwatari

Audio source separation is often used as preprocessing of various applications, and one of its ultimate goals is to construct a single versatile model capable of dealing with the varieties of audio signals.

Audio Source Separation Music Source Separation

HumanACGAN: conditional generative adversarial network with human-based auxiliary classifier and its evaluation in phoneme perception

no code implementations8 Feb 2021 Yota Ueda, Kazuki Fujii, Yuki Saito, Shinnosuke Takamichi, Yukino Baba, Hiroshi Saruwatari

A DNN-based generator is trained using a human-based discriminator, i. e., humans' perceptual evaluations, instead of the GAN's DNN-based discriminator.

Multi-speaker Text-to-speech Synthesis Using Deep Gaussian Processes

no code implementations7 Aug 2020 Kentaro Mitsui, Tomoki Koriyama, Hiroshi Saruwatari

We propose a framework for multi-speaker speech synthesis using deep Gaussian processes (DGPs); a DGP is a deep architecture of Bayesian kernel regressions and thus robust to overfitting.

Gaussian Processes Latent Variable Models +2

Utterance-level Sequential Modeling For Deep Gaussian Process Based Speech Synthesis Using Simple Recurrent Unit

no code implementations22 Apr 2020 Tomoki Koriyama, Hiroshi Saruwatari

This paper presents a deep Gaussian process (DGP) model with a recurrent architecture for speech sequence modeling.

Speech Synthesis

Time-Domain Audio Source Separation Based on Wave-U-Net Combined with Discrete Wavelet Transform

no code implementations28 Jan 2020 Tomohiko Nakamura, Hiroshi Saruwatari

With this belief, focusing on the fact that the DWT has an anti-aliasing filter and the perfect reconstruction property, we design the proposed layers.

Audio Source Separation Music Source Separation

HumanGAN: generative adversarial network with human-based discriminator and its evaluation in speech perception modeling

no code implementations25 Sep 2019 Kazuki Fujii, Yuki Saito, Shinnosuke Takamichi, Yukino Baba, Hiroshi Saruwatari

To model the human-acceptable distribution, we formulate a backpropagation-based generator training algorithm by regarding human perception as a black-boxed discriminator.

V2S attack: building DNN-based voice conversion from automatic speaker verification

no code implementations5 Aug 2019 Taiki Nakamura, Yuki Saito, Shinnosuke Takamichi, Yusuke Ijima, Hiroshi Saruwatari

The experimental evaluation compares converted voices between the proposed method that does not use the targeted speaker's voice data and the standard VC that uses the data.

automatic-speech-recognition Speaker Verification +2

DNN-based Speaker Embedding Using Subjective Inter-speaker Similarity for Multi-speaker Modeling in Speech Synthesis

no code implementations19 Jul 2019 Yuki Saito, Shinnosuke Takamichi, Hiroshi Saruwatari

Although conventional DNN-based speaker embedding such as a $d$-vector can be applied to multi-speaker modeling in speech synthesis, it does not correlate with the subjective inter-speaker similarity and is not necessarily appropriate speaker representation for open speakers whose speech utterances are not included in the training data.

Speech Quality Speech Synthesis

Generative Moment Matching Network-based Random Modulation Post-filter for DNN-based Singing Voice Synthesis and Neural Double-tracking

no code implementations9 Feb 2019 Hiroki Tamaru, Yuki Saito, Shinnosuke Takamichi, Tomoki Koriyama, Hiroshi Saruwatari

To address this problem, we use a GMMN to model the variation of the modulation spectrum of the pitch contour of natural singing voices and add a randomized inter-utterance variation to the pitch contour generated by conventional DNN-based singing voice synthesis.

Singing Voice Synthesis Speech Quality

Phase reconstruction from amplitude spectrograms based on von-Mises-distribution deep neural network

2 code implementations10 Jul 2018 Shinnosuke Takamichi, Yuki Saito, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari

This paper presents a deep neural network (DNN)-based phase reconstruction from amplitude spectrograms.

Sound Audio and Speech Processing

JSUT corpus: free large-scale Japanese speech corpus for end-to-end speech synthesis

no code implementations28 Oct 2017 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 companies has an important role.

Speech Synthesis

Statistical Parametric Speech Synthesis Incorporating Generative Adversarial Networks

4 code implementations23 Sep 2017 Yuki Saito, Shinnosuke Takamichi, Hiroshi Saruwatari

In the proposed framework incorporating the GANs, the discriminator is trained to distinguish natural and generated speech parameters, while the acoustic models are trained to minimize the weighted sum of the conventional minimum generation loss and an adversarial loss for deceiving the discriminator.

Speech Quality Speech Synthesis +1

Sampling-based speech parameter generation using moment-matching networks

no code implementations12 Apr 2017 Shinnosuke Takamichi, Tomoki Koriyama, Hiroshi Saruwatari

To give synthetic speech natural inter-utterance variation, this paper builds DNN acoustic models that make it possible to randomly sample speech parameters.

Speech Quality Speech Synthesis

Voice Conversion Using Sequence-to-Sequence Learning of Context Posterior Probabilities

no code implementations10 Apr 2017 Hiroyuki Miyoshi, Yuki Saito, Shinnosuke Takamichi, Hiroshi Saruwatari

Conventional VC using shared context posterior probabilities predicts target speech parameters from the context posterior probabilities estimated from the source speech parameters.

Speech Recognition Speech Synthesis +1

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