4 citations · 4 across the 3 of their papers we have counts for
5 papers
Deficient Basis Estimation of Noise Spatial Covariance Matrix for Rank-Constrained Spatial Covariance Matrix Estimation Method in Blind Speech Extraction
Yuto Kondo, Yuki Kubo, Norihiro Takamune +2
Rank-constrained spatial covariance matrix estimation (RCSCME) is a state-of-the-art blind speech extraction method applied to cases where one directional target speech and diffuse…
Joint-Diagonalizability-Constrained Multichannel Nonnegative Matrix Factorization Based on Multivariate Complex Sub-Gaussian Distribution
Keigo Kamo, Yuki Kubo, Norihiro Takamune +4
In this paper, we address a statistical model extension of multichannel nonnegative matrix factorization (MNMF) for blind source separation, and we propose a new parameter update a…
Regularized Fast Multichannel Nonnegative Matrix Factorization with ILRMA-based Prior Distribution of Joint-Diagonalization Process
Keigo Kamo, Yuki Kubo, Norihiro Takamune +4
In this paper, we address a convolutive blind source separation (BSS) problem and propose a new extended framework of FastMNMF by introducing prior information for joint diagonaliz…
Acceleration of rank-constrained spatial covariance matrix estimation for blind speech extraction
Yuki Kubo, Norihiro Takamune, Daichi Kitamura +1
In this paper, we propose new accelerated update rules for rank-constrained spatial covariance model estimation, which efficiently extracts a directional target source in diffuse b…
Efficient Full-Rank Spatial Covariance Estimation Using Independent Low-Rank Matrix Analysis for Blind Source Separation
Yuki Kubo, Norihiro Takamune, Daichi Kitamura +1
In this paper, we propose a new algorithm that efficiently separates a directional source and diffuse background noise based on independent low-rank matrix analysis (ILRMA). ILRMA…