output
19972025
most citedPlanck 2018 results. X. Constraints on inflation

2.4k citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing cs.SDShow all

7 papers · 1 filter

cs.SD2021

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…

cs.SD2020★ 30 cited

Consistent Independent Low-Rank Matrix Analysis for Determined Blind Source Separation

Daichi Kitamura, Kohei Yatabe

Independent low-rank matrix analysis (ILRMA) is the state-of-the-art algorithm for blind source separation (BSS) in the determined situation (the number of microphones is greater t…

cs.SD2020★ 4 cited

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…

cs.SD2020

Convergence-guaranteed Independent Positive Semidefinite Tensor Analysis Based on Student's t Distribution

Tatsuki Kondo, Kanta Fukushige, Norihiro Takamune +4

In this paper, we address a blind source separation (BSS) problem and propose a new extended framework of independent positive semidefinite tensor analysis (IPSDTA). IPSDTA is a st…

cs.SD2020

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…

cs.SD2019

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…

cs.SD2018★ 3 cited

Phase reconstruction from amplitude spectrograms based on von-Mises-distribution deep neural network

Shinnosuke Takamichi, Yuki Saito, Norihiro Takamune +2

This paper presents a deep neural network (DNN)-based phase reconstruction from amplitude spectrograms. In audio signal and speech processing, the amplitude spectrogram is often us…