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Shoji Makino

FastMVAE2: On improving and accelerating the fast variational autoencoder-based source separation algorithm for determined mixtures



Li Li , Hirokazu Kameoka , Shoji Makino

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* submit to IEEE/ACM TASLP 
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Speech Enhancement by Noise Self-Supervised Rank-Constrained Spatial Covariance Matrix Estimation via Independent Deeply Learned Matrix Analysis



Sota Misawa , Norihiro Takamune , Tomohiko Nakamura , Daichi Kitamura , Hiroshi Saruwatari , Masakazu Une , Shoji Makino

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* accepted for APSIPA2021 
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Fast MVAE: Joint separation and classification of mixed sources based on multichannel variational autoencoder with auxiliary classifier



Li Li , Hirokazu Kameoka , Shoji Makino

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* Submitted to ICASSP 2019 
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Semi-blind source separation with multichannel variational autoencoder



Hirokazu Kameoka , Li Li , Shota Inoue , Shoji Makino

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Multi-command Chest Tactile Brain Computer Interface for Small Vehicle Robot Navigation



Hiromu Mori , Shoji Makino , Tomasz M. Rutkowski

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* accepted as a full paper for The 2013 International Conference on Brain and Health Informatics; to appear in Lecture Notes in Computer Science (LNCS), Springer Verlag Berlin Heidelberg, 2013; http://link.springer.com/ 
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