| 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 # | |
| SP, IPSJ-SLP, EA, SIP [detail] | 2023-03-01 09:50 |
Okinawa | (Primary: On-site, Secondary: Online) |
Regularization Term Design Based on Spectrogram Consistency in Independent Low-Rank Matrix Analysis for Multichannel Audio Source Separation Sota Misawa, Norihiro Takamune (UTokyo), Kohei Yatabe (TUAT), Daichi Kitamura (NIT, Kagawa), Hiroshi Saruwatari (UTokyo)  EA2022-105 SIP2022-149 SP2022-69 |
It is known that block permutation occurs in the separated signals obtained by independent low-rank matrix analysis. Rec... [more] | EA2022-105 SIP2022-149 SP2022-69 pp.177-184 |
| SP, IPSJ-MUS, IPSJ-SLP [detail] | 2022-06-17 13:00 |
Online | Online | SP2022-6 |
Rank-constrained spatial covariance matrix estimation (RCSCME) is a method for blind speech extraction. In RCSCME, we de... [more] | SP2022-6 pp.18-23 |
| 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 |
| 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 |
| EA, SIP, SP | 2019-03-14 15:15 |
Nagasaki | i+Land nagasaki (Nagasaki-shi) | Convergence-guaranteed independent positive semidefinite tensor analysis for blind source separation Kanta Fukushige, Norihiro Takamune (UTokyo), Daichi Kitamura (Kagawa-NICT), Hiroshi Saruwatari (UTokyo), Rintaro Ikeshita, Tomohiro Nakatani (NTT) EA2018-127 SIP2018-133 SP2018-89 |
This paper focuses on independent positive semidefinite tensor analysis (IPSDTA), which is a technique for over-determin... [more] | EA2018-127 SIP2018-133 SP2018-89 pp.167-172 |
| 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 |
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 10:00 |
Okinawa | Experimental Evaluation of Multichannel Audio Source Separation Based on IDLMA Daichi Kitamura, Hayato Sumino, Norihiro Takamune, Shinnosuke Takamichi, Hiroshi Saruwatari (Univ. of Tokyo), Nobutaka Ono (Tokyo Metropolitan Univ.) EA2017-104 SIP2017-113 SP2017-87 |
In this paper, we propose a new informed multichannel audio source separation called independent deeply learned matrix a... [more] | EA2017-104 SIP2017-113 SP2017-87 pp.13-20 |
|
| EA, ASJ-H | 2017-07-21 13:40 |
Hokkaido | Hokkaido Univ. | [Poster Presentation]
ILRMA with complex Student's t source model Shinichi Mogami, Daichi Kitamura, Norihiro Takamune, Yoshiki Mitsui, Hiroshi Saruwatari (Univ. of Tokyo), Nobutaka Ono (NII), Yu Takahashi, Kazunobu Kondo (Yamaha) EA2017-23 |
(To be available after the conference date) [more] | EA2017-23 pp.131-136 |
| EA | 2015-12-11 15:15 |
Ishikawa | Kanazawa Univ., Satellite Plaza | [Poster Presentation]
Analysis on Degree of Freedom for Supervised NMF with All-Pole-Model-Based Basis Deformation Hiroaki Nakajima (UTokyo), Daichi Kitamura (SOKENDAI), Norihiro Takamune, Shoichi Koyama, Hiroshi Saruwatari (UTokyo), Nobutaka Ono (NII/SOKENDAI), Yu Takahashi, Kazunobu Kondo (Yamaha) EA2015-42 |
Conventional supervised NMF has the critical problem that a mismatch between the bases trained in advance and the target... [more] | EA2015-42 pp.13-18 |
| IBISML | 2014-11-17 17:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Training Algorithm for Restricted Boltzmann Machines Using Auxiliary Function Approach Norihiro Takamune (Univ. of Tokyo), Hirokazu Kameoka (Univ. of Tokyo/NTT) IBISML2014-56 |
Layerwise pre-training is one of important elements for deep learning, and Restricted Boltzmann Machines (RBMs) is popul... [more] | IBISML2014-56 pp.161-168 |
| 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 |
|
[Return to Top Page]