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Yu Nakagome

2 accepted papers

2020

Deep Speech Extraction with Time-Varying Spatial Filtering Guided By Desired Direction Attractor

Yu Nakagome, Masahito Togami, Tetsuji Ogawa, Tetsunori Kobayashi
ICASSP 2020accepted

In this investigation, a deep neural network (DNN) based speech extraction method is proposed to enhance a speech signal propagating from the desired direction. The proposed method integrates knowledge based on a sound propagation model and the time-varying characteristics of a speech source, into a…

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2020

Unsupervised Training for Deep Speech Source Separation with Kullback-Leibler Divergence Based Probabilistic Loss Function

Masahito Togami, Yoshiki Masuyama, Tatsuya Komatsu, Yu Nakagome
ICASSP 2020accepted

In this paper, we propose a multi-channel speech source separation method with a deep neural network (DNN) which is trained under the condition that no clean signal is available. As an alternative to a clean signal, the proposed method adopts an estimated speech signal by an unsupervised speech sour…

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