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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-04 10:15 |
Online | Online | A quantitative measure of discriminability between NMF dictionaries Eisuke Konno, Daisuke Saito, Nobuaki Minematsu (UTokyo)  EA2020-82 SIP2020-113 SP2020-47 |
Supervised nonnegative matrix factorization (NMF) is a popular approach for monaural audio source separation. It realize... [more] | EA2020-82 SIP2020-113 SP2020-47 pp.134-139 |
| SP, EA, SIP | 2020-03-03 09:00 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
Semi-supervised Self-produced Speech Enhancement and Suppression Based on Joint Source Modeling of Air- and Body-conducted Signals Using Variational Autoencoder Shogo Seki, Moe Takada, Kazuya Takeda, Tomoki Toda (Nagoya Univ.) EA2019-140 SIP2019-142 SP2019-89 |
This paper proposes a semi-supervised method for enhancing and suppressing self-produced speech, using a variational aut... [more] | EA2019-140 SIP2019-142 SP2019-89 pp.225-230 |
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 13:00 |
Okinawa | [Poster Presentation]
Sound Source Separation Using Supervised NMF Based on One-dimensional Oblique Projections Misaki Komatsu, Akira Tanaka (Hokkaido Univ.) EA2017-124 SIP2017-133 SP2017-107 |
In the conventional supervised NMF, mutual relationship between given basis vectors is not considered appropriately, wh... [more] |
EA2017-124 SIP2017-133 SP2017-107 pp.133-134 |
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| EA, SP, SIP | 2016-03-29 13:15 |
Oita | Beppu International Convention Center B-ConPlaza | Effective basis learning for sound source separation by semi-supervised nonnegative matrix factorization Daichi Kitamura (SOKENDAI), Nobutaka Ono (NII/SOKENDAI), Hiroshi Saruwatari (UT), Yu Takahashi, Kazunobu Kondo (Yamaha) EA2015-130 SIP2015-179 SP2015-158 |
This paper addresses a sound source separation problem and proposes an effective basis learning method for semi-supervis... [more] | EA2015-130 SIP2015-179 SP2015-158 pp.355-360 |
| IBISML | 2013-11-13 15:45 |
Tokyo | Tokyo Institute of Technology, Kuramae-Kaikan | [Poster Presentation]
Energy Disaggregation for Appliance Loads Based on Semi-Supervised NMF Yu Fujimoto, Naoki Okubo, Yasuhiro Hayashi (Waseda Univ.), Yoshimasa Sugitate, Shiro Ogata (Omron) IBISML2013-60 |
The authors propose an application of non-negative matrix factorization for the energy disaggregation task. The method i... [more] | IBISML2013-60 pp.185-190 |
| SIP, CAS, CS | 2013-03-14 12:00 |
Yamagata | Keio Univ. Tsuruoka Campus (Yamagata) | SUPERVISED NMF AS A SPARSE OPTIMIZATION PROBLEM Yu Morikawa, Masahiro Yukawa (Niigata Univ.) CAS2012-114 SIP2012-145 CS2012-120 |
In this paper, we propose a novel scheme to supervised nonnegative matrix factorization (NMF). We formulate the supervi... [more] |
CAS2012-114 SIP2012-145 CS2012-120 pp.105-109 |
| US, EA (Joint) |
2013-01-24 11:20 |
Kyoto | Kambaikan, Doshisha Univ. | Signal separation for real instruments based on supervised NMF with basis deformation Daichi Kitamura, Hiroshi Saruwatari, Kiyohiro Shikano (NAIST), Kazunobu Kondo, Yu Takahashi (Yamaha) EA2012-121 |
Nonnegative Matrix Factorization (NMF) is one of the technique used for separation of an audio mixture that consists of ... [more] | EA2012-121 pp.13-18 |
| SP | 2011-07-23 09:55 |
Hokkaido | Jozankei Grand Hotel | Constrained Spectrum Generation for Mixed Sound Analysis Based on Probabilistic Spectrum Envelope Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki (Kobe Univ.) SP2011-50 |
NMF (Non-negative matrix factorization) has been one of the most widely-used techniques for signal analysis in recent ye... [more] | SP2011-50 pp.51-56 |
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