14 citations · 60 across the 18 of their papers we have counts for
15 papers · 1 filter
WaveFit: An Iterative and Non-autoregressive Neural Vocoder based on Fixed-Point Iteration
Yuma Koizumi, Kohei Yatabe, Heiga Zen +1
Denoising diffusion probabilistic models (DDPMs) and generative adversarial networks (GANs) are popular generative models for neural vocoders. The DDPMs and GANs can be characteriz…
Wearable SELD dataset: Dataset for sound event localization and detection using wearable devices around head
Kento Nagatomo, Masahiro Yasuda, Kohei Yatabe +2
Sound event localization and detection (SELD) is a combined task of identifying the sound event and its direction. Deep neural networks (DNNs) are utilized to associate them with t…
APPLADE: Adjustable Plug-and-play Audio Declipper Combining DNN with Sparse Optimization
Tomoro Tanaka, Kohei Yatabe, Masahiro Yasuda +1
In this paper, we propose an audio declipping method that takes advantages of both sparse optimization and deep learning. Since sparsity-based audio declipping methods have been de…
Noisy-target Training: A Training Strategy for DNN-based Speech Enhancement without Clean Speech
Takuya Fujimura, Yuma Koizumi, Kohei Yatabe +1
Deep neural network (DNN)-based speech enhancement ordinarily requires clean speech signals as the training target. However, collecting clean signals is very costly because they mu…
Gamma Boltzmann Machine for Simultaneously Modeling Linear- and Log-amplitude Spectra
Toru Nakashika, Kohei Yatabe
In audio applications, one of the most important representations of audio signals is the amplitude spectrogram. It is utilized in many machine-learning-based information processing…
Consistent ICA: Determined BSS meets spectrogram consistency
Kohei Yatabe
Multichannel audio blind source separation (BSS) in the determined situation (the number of microphones is equal to that of the sources), or determined BSS, is performed by multich…