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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 21 - 40 of 113 [Previous]  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
SP, EA, SIP 2020-03-02
10:10
Okinawa Okinawa Industry Support Center
(Cancelled but technical report was issued)
Multichannel NMF with Joint-Diagonalizable Constraint Based on Generalized Gaussian Distribution for Blind Source Separation
Keigo Kamo, Yuki Kubo, Norihiro Takamune (UTokyo), Daichi Kitamura (NIT Kagawa), Hiroshi Saruwatari (UTokyo), Yu Takahashi, Kazunobu Kondo (Yamaha) EA2019-103 SIP2019-105 SP2019-52
Multichannel nonnegative matrix factorization (MNMF) is a blind source separation technique, which employs the full-rank... [more] EA2019-103 SIP2019-105 SP2019-52
pp.13-19
IT, SIP, RCS 2020-01-23
09:50
Hiroshima Hiroshima City Youth Center A Study on Channel Estimation by Using Independent Component Analysis in Large-scale MIMO Systems
Taichi Kasai, Shinsuke Ibi, Hisato Iwai, Hideichi Sasaoka (Doshisha Univ.) IT2019-37 SIP2019-50 RCS2019-267
As the demand for wireless communication technology increases, efficient frequency usage is required. In the case of lar... [more] IT2019-37 SIP2019-50 RCS2019-267
pp.7-11
EA 2019-12-13
13:25
Fukuoka Kyushu Inst. Tech. Rank-constrained spatial covariance matrix estimation based on multivariate complex generalized Gaussian distribution and its acceleration for blind speech extraction
Yuki Kubo, Norihiro Takamune (UTokyo), Daichi Kitamura (NIT, Kagawa), Hiroshi Saruwatari (UTokyo) EA2019-78
In this paper, we generalize a generative model in rank-constrained spatial covariance matrix estimation that separates ... [more] EA2019-78
pp.85-92
EA, ASJ-H 2019-10-28
14:00
Tokyo NHK Science&Technology Research Lab. FastMNMF based on multivariant complex Student's t distribution for blind source separation
Keigo Kamo, Yuki Kubo, Norihiro Takamune (UTokyo), Daichi Kitamura (Kagawa NCIT), Hiroshi Saruwatari (UTokyo), Yu Takahashi, Kazunobu Kondo (Yamaha) EA2019-40
FastMNMF is a blind source separation technique, which is an accelerated algorithm of multichannel nonnegative matrix fa... [more] EA2019-40
pp.23-29
RCS 2019-04-19
10:55
Hokkaido Noboribetsu Grand Hotel Blind Source Separation in Nonlinear Mixture: Separation and a Multi-Subspace Representation
Lu Wang, Tomoaki Ohtsuki (Keio Univ.) RCS2019-16
The process deals with blind source separation in the nonlinear domain is to estimate the original signals or mixture fu... [more] RCS2019-16
pp.73-78
EA, SIP, SP 2019-03-14
10:25
Nagasaki i+Land nagasaki (Nagasaki-shi) Blind speech separation based on approximate joint diagonalization utilizing correlation between neighboring frequency bins
Taiki Asamizu, Toshihiro Furukawa (TUS) EA2018-100 SIP2018-106 SP2018-62
In this paper, we propose a new method that extends the approximate joint diagonalization blind speech separation (BSS).... [more] EA2018-100 SIP2018-106 SP2018-62
pp.7-12
EA, SIP, SP 2019-03-14
15:40
Nagasaki i+Land nagasaki (Nagasaki-shi) Estimation of rank-constrained spatial covariance model based on multivariate complex Student's t distribution for blind source separation
Yuki Kubo, Norihiro Takamune (UTokyo), Daichi Kitamura (Kagawa NCIT), Hiroshi Saruwatari (UTokyo) EA2018-128 SIP2018-134 SP2018-90
In this paper, we generalize a generative model in estimation of rank-constrained spatial covariance model that separate... [more] EA2018-128 SIP2018-134 SP2018-90
pp.173-178
EA, SIP, SP 2019-03-15
11:25
Nagasaki i+Land nagasaki (Nagasaki-shi) [Invited Talk] Realization of real-time blind source separation with auxiliary-function-based algorithms
Nobutaka Ono (TMU) EA2018-133 SIP2018-139 SP2018-95
Blind source separation is a signal processing technique to estimate sound source signals only from the observation of m... [more] EA2018-133 SIP2018-139 SP2018-95
p.203
RCS, SR, SRW
(Joint)
2019-03-06
10:55
Kanagawa YRP Performance Analysis for Nonlinear Separation Model with a Flexible Approximation
Lu Wang, Tomoaki Ohtsuki (Keio Univ.) RCS2018-292
The process deals with blind source separation in the nonlinear domain is to estimate the original signals or mixture fu... [more] RCS2018-292
pp.61-66
NC, MBE
(Joint)
2019-03-05
11:10
Tokyo University of Electro Communications Unsupervised blind source separation using self conditioned entropy minimization
Yuan-chieh Ling, Toshitake Asabuki (UTokyo), Tomoki Fukai (RIKEN CBS) NC2018-67
Unsupervised blind source separation refers to extracting underlying source signals from mixed signals without additiona... [more] NC2018-67
pp.127-129
SIS, ITE-BCT 2018-10-25
10:00
Kyoto Kyoto University Clock Tower Centennial Hall Accuracy Analysis of Background Noise Estimation Using Outer Product Expansion with Lower Norm
Kouta Sugiura, Akitoshi Itai (Chubu Univ.) SIS2018-10
In this paper, the background noise estimation using outer product expansion is developed.
We have shown that a possib... [more]
SIS2018-10
pp.1-5
SIP, EA, SP, MI
(Joint) [detail]
2018-03-19
09:00
Okinawa   Adaptive BSS algorithm for approximate joint diagonalization with variable epoch length
Kei Nishiyama, Shinya Saito (TUS), Kunio Oishi (TUT), Toshihiro Furukawa (TUS) EA2017-102 SIP2017-111 SP2017-85
This paper presents an adaptive blind speech separation (BSS) technique for recovering original speech source signals fr... [more] EA2017-102 SIP2017-111 SP2017-85
pp.1-6
EA, ASJ-H 2017-12-01
14:20
Overseas University of Auckland (New Zealand) [Invited Talk] Blind Audio Source Separation based on Independent Component Analysis
Shoji Makino (Univ. of Tsukuba) EA2017-78
This talk describes a method for the blind source separation (BSS) of convolutive mixtures of audio signals, especially ... [more] EA2017-78
p.107
MBE, NC
(Joint)
2017-11-25
15:10
Miyagi Tohoku University Ensemble Learning with Feature Extraction for EEG Signal Discrimination using Source Separation
Shuichi Nishino, Tomohiro Yoshikawa, Takeshi Furuhashi (Nagoya Univ.) NC2017-36
BCI allows a user to control external devices and to communicate with other people by measuring and discriminating EEG. ... [more] NC2017-36
pp.49-52
SP 2017-08-30
11:00
Kyoto Kyoto Univ. [Poster Presentation] Semi-blind speech separation and enhancement using recurrent neural network
Masaya Wake, Yoshiaki Bando, Masato Mimura, Katsutoshi Itoyama, Kazuyoshi Yoshii, Tatsuya Kawahara (Kyoto Univ.) SP2017-22
This paper describes a semi-blind speech enhancement method using a neural network.
In a human-robot speech interaction... [more]
SP2017-22
pp.13-18
EA, SP, SIP 2016-03-28
13:15
Oita Beppu International Convention Center B-ConPlaza [Poster Presentation] Convolutive Blind Source Separation with multi-stage Approximate Joint Diagonalization
Toshiki Mori, Shinya Saito (TUS), Kunio Oishi (Tokyo Univ. of Tech.), Tosihiro Furukawa (TUS) EA2015-76 SIP2015-125 SP2015-104
In this paper, we present an approach of recovering signal waveforms of speech sources from observed signals in noisy
a... [more]
EA2015-76 SIP2015-125 SP2015-104
pp.57-62
EA, EMM 2015-11-12
17:00
Kumamoto Kumamoto Univ. Noise suppression method for body-conducted soft speech based on external noise monitoring
Yusuke Tajiri (NAIST), Tomoki Toda (Nagoya Univ.), Satoshi Nakamura (NAIST) EA2015-31 EMM2015-52
As one of the silent speech interfaces, nonaudible murmur (NAM) microphone has been developed for detecting an extremely... [more] EA2015-31 EMM2015-52
pp.41-46
SIP, EA, SP 2015-03-02
09:50
Okinawa   Unified approach for BSS, DOA estimation, audio event detection and dereverberation with multichannel factorial HMM and DOA mixture model
Takuya Higuchi (Univ. of Tokyo), Hirokazu Kameoka (Univ. of Tokyo/ NTT) EA2014-74 SIP2014-115 SP2014-137
We deal with the problems of blind source separation, dereverberation, audio event detection and DOA estimation. We prev... [more] EA2014-74 SIP2014-115 SP2014-137
pp.13-18
IBISML 2014-11-17
17:00
Aichi Nagoya Univ. [Poster Presentation] Unified approach for auditory scene analysis based on multichannel factorial hidden Markov model
Takuya Higuchi (Univ. of Tokyo), Hirokazu Kameoka (Univ. of Tokyo/NTT) IBISML2014-57
This paper deals with the problems of audio source separation, audio event detection, dereverberation and DOA estimation... [more] IBISML2014-57
pp.169-176
MBE 2014-05-24
14:50
Toyama University of Toyama Separation of artifacts mixed in the EEGs when eating with use of independent vector analysis (IVA)
Shigeru Tominaga (Meiji), Hisashi Yoshida, Noboru Nakasako (Kinki Univ.) MBE2014-8
In feeling estimation while eating by use of EEG, removing artifacts induced by principally masticatory muscular activit... [more] MBE2014-8
pp.37-42
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