Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
SIP |
2022-08-26 11:06 |
Okinawa |
Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Initialization-robust blind synchronization of multiple microphones by incrementally widening frequency-band used in likelihood function Yoshiki Masuyama, Kouei Yamaoka, Nobutaka Ono (TMU) SIP2022-66 |
Asynchronous distributed microphone array, which is constructed by microphones on different devices, has gained much att... [more] |
SIP2022-66 pp.86-90 |
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, 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 |
TL |
2018-03-19 14:30 |
Tokyo |
Waseda University |
Duality of the Passage of Time Impacting Auxiliary Verb “会”
-- An Error Analysis of "Future Expression" in Japanese CFL (Chinese as a foreign language) Learners -- Tomohiro Ishida, Hiroshi Sano (TUFS) TL2017-67 |
Learner's corpus analysis has revealed that the acquisition of the Chinese auxiliary verb 会(hui) which represents “possi... [more] |
TL2017-67 pp.45-50 |
EA, SP, SIP |
2016-03-28 13:15 |
Oita |
Beppu International Convention Center B-ConPlaza |
[Poster Presentation]
Super-Resolution Vocal Tract Spectrum Estimation with Missing Data Imputation Using Non-Negative Matrix Factorization Tomohiko Nakamura (Todai), Hirokazu Kameoka (Todai/NTT) EA2015-83 SIP2015-132 SP2015-111 |
This report addresses the problem of estimating vocal tract spectra from speech signals. Spectra of speech signals can b... [more] |
EA2015-83 SIP2015-132 SP2015-111 pp.99-104 |
EA, SP, SIP |
2016-03-29 09:00 |
Oita |
Beppu International Convention Center B-ConPlaza |
[Poster Presentation]
Amplitude limiters based on phase optimization Akira Kakitani, Daisuke Saito, Yasuhiro Kosugi, Nobuaki Minematsu (UTokyo) EA2015-111 SIP2015-160 SP2015-139 |
In order to reduce the peak value of source waveforms without quality degradation, a novel method is proposed. In this m... [more] |
EA2015-111 SIP2015-160 SP2015-139 pp.249-254 |
NC, IPSJ-BIO, IBISML, IPSJ-MPS (Joint) [detail] |
2015-06-23 10:45 |
Okinawa |
Okinawa Institute of Science and Technology |
A Study on Non-negative Matrix Factorization for Integrated Analysis of Visiting and Rating Information Masahiro Kohjima, Tatsushi Matsubayashi, Hiroshi Sawada (NTT) IBISML2015-4 |
As the number of projects on data collection and analysis increases in many business fields, it is required that the met... [more] |
IBISML2015-4 pp.21-26 |
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 |
2014-02-28 13:50 |
Tokushima |
The University of Tokushima |
[Invited Talk]
Non-negative matrix factorization and its applications to time series processing Hirokazu Kameoka (Univ. Tokyo/NTT) SP2013-116 |
In this paper, I will give a brief introduction to a data analysis technique called non-negative matrix factorization (N... [more] |
SP2013-116 pp.31-36 |
PRMU, IPSJ-CVIM, MVE [detail] |
2014-01-23 10:00 |
Osaka |
|
Minimum Classification Error Training with Automatic Control of Loss Smoothness Hideaki Tanaka (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-92 MVE2013-33 |
The Minimum Classification Error (MCE) training has been successfully applied to various types of classifiers. However, ... [more] |
PRMU2013-92 MVE2013-33 pp.7-12 |
PRMU, IPSJ-CVIM, MVE [detail] |
2014-01-23 10:30 |
Osaka |
|
Multi-Class Support Vector Machine based on Minimum Classification Error Criterion Hisashi Uehara (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-93 MVE2013-34 |
Gradient-descent-based optimization methods used in Minimum Classification Error (MCE) training are not necessarily easi... [more] |
PRMU2013-93 MVE2013-34 pp.13-18 |
SP, EA, SIP |
2013-05-16 13:00 |
Okayama |
|
[Invited Talk]
Fast Blind Source Separation Based on Auxiliary-function-based Independent Vector Analysis Nobutaka Ono (NII) EA2013-5 SIP2013-5 SP2013-5 |
In this paper, the fast and stable blind source separation algorithm, which is derived by applying auxiliary function me... [more] |
EA2013-5 SIP2013-5 SP2013-5 pp.25-30 |
EA |
2012-12-14 14:20 |
Tokyo |
National Institute of Informatics |
[Invited Talk]
Non-negative matrix factorization and its applications to audio signal processing Hirokazu Kameoka (University of Tokyo/NTT) EA2012-118 |
In this paper, I will give a brief introduction to a data analysis technique called non-negative matrix factorization (N... [more] |
EA2012-118 pp.53-58 |
CS, SIP, CAS |
2011-03-03 09:40 |
Okinawa |
Ohhamanobumoto memorial hall (Ishigaki)( |
NMF Considering Given Vectors in a Basis Yuta Amano, Akira Tanaka, Masaaki Miyakoshi (Hokkaido Univ) CAS2010-125 SIP2010-141 CS2010-95 |
Recently, a novel matrix factorization, named non-negarive matrix factorization (NMF), attracts much attention in the fi... [more] |
CAS2010-125 SIP2010-141 CS2010-95 pp.137-141 |
EA |
2009-11-20 11:00 |
Hiroshima |
|
Dynamics Properties of Active Noise Control with Auxiliary Noise Scaled by Residual Noise Signal Jian Liu, Yegui Xiao, Akira Ikuta (Pref Univ. of Hiroshima.) EA2009-87 |
In an active noise control (ANC) system with online secondary-path modeling based on auxiliary white noise injection, th... [more] |
EA2009-87 pp.67-72 |