| IEICE Technical Committee Submission System Conference Schedule |
Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| 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 |
| SP, IPSJ-MUS | 2014-05-24 11:30 |
Tokyo | Underdetermined Blind Separation of Moving Sources Based on Probabilistic Modeling Takuya Higuchi, Norihiro Takamune, Tomohiko Nakamura (Univ. of Tokyo), Hirokazu Kameoka (Univ. of Tokyo/NTT) SP2014-20 |
This paper deals with the problem of the underdetermined blind separation and tracking of moving sources. In practical s... [more] | SP2014-20 pp.211-216 |
|
| IBISML | 2014-03-07 11:10 |
Nara | Nara Women's University | Blind Separation of Sparse and Smooth Signals via Approximate Message Passing Algorithm Shigeki Yokoyama, Toshiyuki Tanaka (Kyoto Univ.) IBISML2013-76 |
We consider the problem to recover source signals from noisy mixed ones. This can be described as a matrix reconstructio... [more] | IBISML2013-76 pp.71-78 |
| SIS | 2013-12-12 13:00 |
Tottori | Torigin Bunka Kaikan (Tottori) | [Tutorial Lecture]
Enhancement and Separation for Speech Signals Arata Kawamura (Osaka Univ.) SIS2013-35 |
In this paper, we discus about three main topics of speech processing technologies. First, we review and discuss about a... [more] | SIS2013-35 pp.47-52 |
| SP, EA, SIP | 2013-05-16 10:55 |
Okayama | Permutation-free clustering-based source separation based on time-varying mixture weights Nobutaka Ito, Shoko Araki, Tomohiro Nakatani (NTT) EA2013-2 SIP2013-2 SP2013-2 |
To avoid the permutation problem in clustering-based source separation, we introduce a mixture model with time-varying, ... [more] | EA2013-2 SIP2013-2 SP2013-2 pp.7-12 |
|
| NLP | 2013-03-14 10:20 |
Chiba | Nishi-Chiba campus, Chiba Univ. | A Nonlinear Blind Source Separation using a Ring Particle Swarm Optimization Algorithm Takuya Kurihara, Kenya Jin'no (Nippon Inst. of Tech) NLP2012-146 |
Blind source separation (BSS) is a technique for recovering an original source signal from mixing signals without the ai... [more] | NLP2012-146 pp.13-18 |
[Return to Top Page]