Yoshiki Mitsui — accepted AI-conference papers

2018

Vectorwise Coordinate Descent Algorithm for Spatially Regularized Independent Low-Rank Matrix Analysis

Yoshiki Mitsui, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari, Yu Takahashi, Kazunobu Kondo

ICASSP 2018accepted

Audio source separation is an important problem for many audio applications. Independent low-rank matrix analysis (ILRMA) is a recently proposed algorithm that employs the statistical independence between sources and the low-rankness of the time-frequency structure in each source. As reported in thi…

Cited by 0 Source ↗Scholar ↗

2017

Blind source separation based on independent low-rank matrix analysis with sparse regularization for time-series activity

Yoshiki Mitsui, Daichi Kitamura, Shinnosuke Takamichi, Nobutaka Ono, Hiroshi Saruwatari

ICASSP 2017accepted

In this paper, we propose a new blind source separation (BSS) method based on independent low-rank matrix analysis (ILRMA) with novel sparse regularization. ILRMA is a recently proposed BSS algorithm that simultaneously estimates a demixing matrix and source spectrogram models based on nonnegative m…

Cited by 0 Source ↗Scholar ↗