IEICE Technical Committee Submission System
Conference Schedule
Online Proceedings
[Sign in]
Tech. Rep. Archives
    [Japanese] / [English] 
( Committee/Place/Topics  ) --Press->
 
( Paper Keywords:  /  Column:Title Auth. Affi. Abst. Keyword ) --Press->

All Technical Committee Conferences  (Searched in: All Years)

Search Results: Conference Papers
 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 21 - 40 of 50 [Previous]  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
SIS, IPSJ-AVM 2015-09-03
11:20
Osaka Kansai Univ. A Sequential Processing Model for Speech Separation Based on Auditory Scene Analysis
Isao Nakanishi, Junichi Hanada, Misaki Baba (Tottori Univ.) SIS2015-16
Speech separation based on auditory scene analysis (ASA) has been widely studied.
We propose a processing method of the... [more]
SIS2015-16
pp.7-12
EA 2014-10-24
14:20
Tokyo Central Research Laboratory, Hitachi, Ltd. [Invited Talk] Speech enhancement techniques in multi-speaker spontaneous speech recognition for conversation scene analysis
Shoko Araki, Takaaki Hori, Tomohiro Nakatani (NTT) EA2014-25
This paper illustrates speech enhancement techniques for multi-speaker distant-talk speech recognition, where a conversa... [more] EA2014-25
pp.9-14
SIP 2014-08-28
16:55
Osaka Ritsumeikan Univ. (Osaka Umeda Campus) A Method for Sequential Speech Separation Based on Auditory Scene Analysis
Junichi Hanada, Isao Nakanishi, Shigang Li (Tottori Univ.) SIP2014-80
We propose a sequentially processing method of the speech separation based on auditory scene analysis (ASA). [more] SIP2014-80
pp.37-42
SP, WIT, ASJ-H 2014-06-20
10:25
Ishikawa   Accurate Recognition of Overlapped Speech -- High Speed Speech Separation by Spectral Subtraction and Acoustic Model Training using Separated Speeches --
Yuto Dekiura, Tetsuya Matsumoto, Yoshinori Takeuchi, Hiroaki Kudo, Noboru Ohnishi, Norihide Kitaoka, Kazuya Takeda (Nagoya Univ.) SP2014-56 WIT2014-11
The purpose of this study is to recognize overlapped speech more accurately. In order to achieve this, it is necessary t... [more] SP2014-56 WIT2014-11
pp.57-62
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 2013-05-17
13:25
Okayama   Online independent vector analysis with incremental updates of weighted covariance
Toru Taniguchi (Toshiba), Nobutaka Ono (NII), Akinori Kawamura (Toshiba), Shigeki Sagayama (NII) EA2013-21 SIP2013-21 SP2013-21
We proposed a method of online independent vector analysis based on an
auxiliary-function approach, proposed by N. Ono,... [more]
EA2013-21 SIP2013-21 SP2013-21
pp.121-126
SP, IPSJ-SLP 2012-12-21
14:40
Tokyo TITECH(Ookayama) Reduction of cross spectrum for feature-domain sound source separation
Atsushi Ando (Nagoya Univ.), Kenta Niwa (NTT), Norihide Kitaoka, Kazuya Takeda (Nagoya Univ.) SP2012-93
Speech source separation is utilized for recognition of simultaneous speech. Conventional source separation methods, esp... [more] SP2012-93
pp.107-112
EA, EMM 2012-11-16
12:10
Oita OITA Univ. Auxiliary-function-based independent vector analysis with non-speech frame information for speech enhancement
Masataka Suzuki (Univ. of Tokyo), Nobutaka Ono (NII), Toru Taniguchi, Masaru Sakai, Akinori Kawamura (Toshiba Corp.), Miquel Espi, Shigeki Sagayama (Univ. of Tokyo) EA2012-87 EMM2012-69
In this study, we discuss a technique to enhance the speech of interest in the noisy environment with using microphone a... [more] EA2012-87 EMM2012-69
pp.35-38
PRMU, SP 2012-02-10
15:20
Miyagi   Multi-band speech recognition using confidence of blind source separation
Atsushi Ando, Hiromasa Ohashi (Nagoya Univ.), Sunao Hara (NAIST), Norihide Kitaoka, Kazuya Takeda (Nagoya Univ.) PRMU2011-234 SP2011-149
One of the main applications of Blind Source Separation (BSS) is to improve performance of Automatic Speech Recognition ... [more] PRMU2011-234 SP2011-149
pp.219-224
EA 2011-03-18
10:00
Aichi Nagoya Univ. Tiny-setup Blind Source Separation via Time-Varying Softmask based on Alternative Separation Matrix
Kazunobu Kondo, Yu Takahashi, Seiichi Hashimoto (Yamaha Corp.), Takanori Nishino (Mie Univ.), Kazuya Takeda (Nagoya Univ.) EA2010-126
Frequency domain independent component analyis has received much attention from many industries for high performace spee... [more] EA2010-126
pp.1-6
SP 2011-01-27
14:00
Kyoto NICT [Invited Talk] Robot Audition -- Hands-Free Automatic Speech Recognition under Highly-Noisy Environemnts --
Kazuhiro Nakadai (HRI-JP/Tokyo Tech.), Hiroshi G. Okuno (Kyoto Univ.) SP2010-104
This paper addresses robot audition, which realizes listening capabilities for robots using robot-embedded microphones. ... [more] SP2010-104
pp.7-12
SP 2011-01-27
15:45
Kyoto NICT Relation between musical noise generation in nonlinear signal processing and speech recognition performance
Ryoichi Miyazaki, Takayuki Inoue, Nobuhisa Hirata, Hiroshi Saruwatari, Kiyohiro Shikano (NAIST), Tomoya Takatani (TOYOTA) SP2010-106
In this paper, we discuss a relation between musical noise generation in nonlinear signal processing and
speech recogni... [more]
SP2010-106
pp.19-24
SP 2010-11-19
09:15
Aichi Aichi Prefectural Univ. Acoustic separation between linguistic and extra-linguistic information in speech and its significant importance to enable speech communication
Nobuaki Minematsu (Univ. Tokyo) SP2010-78
The source-filter model, which was derived from observations of speech production, has been widely used to separate spee... [more] SP2010-78
pp.53-58
SP, EA, SIP 2010-05-26
13:25
Hyogo Konan Univ. (Hirao Seminar House) Online Speech Separation based on Spectral Subtraction for Meeting Speech Recognition
Yu Nasu, Koichi Shinoda, Sadaoki Furui (Tokyo Inst. of Tech.) EA2010-2 SIP2010-2 SP2010-2
This paper proposes a speech separation method for meeting speech recognition, which operates in real time. The proposed... [more] EA2010-2 SIP2010-2 SP2010-2
pp.7-12
CAS 2010-01-28
13:00
Kyoto Kyoudai-Kaikan Bldg. A Study on Adjustment Method to Noise Spectral Shape for Sub-Band Subspace Approach
Suguru Imai, Atsushi Nakagaki, Koji Shibata (Kitami Inst. of Tech.) CAS2009-64
An adjustment method of sub-band separation is proposed for enhancement of speech degraded by colored noises. A signal s... [more] CAS2009-64
pp.1-6
SP 2009-11-26
14:00
Shizuoka Shizuoka University Voice Production Model Considering Boundary-layer Analysis of Glottal Flow and Source-filter Interactions
Tokihiko Kaburagi, Katsunori Daimo (Kyushu Univ.) SP2009-64
This paper presents an estimating method of the glottal volume flow by considering the influence of air viscosity and in... [more] SP2009-64
pp.13-18
EA 2009-06-26
16:30
Hokkaido   A study of acoustic simulation for humanoid robot
Kiyoshi Yamamoto, Futoshi Asano, Yosuke Matsusaka, Isao Hara, Hideki Asoh (AIST), Makoto Otani, Yukio Iwaya (Tohoku Univ.) EA2009-35
It is important to evaluate speech interface in real environment. However, it is difficult to provide diverse environmen... [more] EA2009-35
pp.103-108
SIS 2009-03-06
10:30
Tokyo   A Method of Blind Source Separation for Mixed Voice Separation in Noisy and Reverberating Environment -- Introduction of Genetic Algorithm --
Masato Katou, Kaoru Arakawa (Meiji Univ.)
Various methods have been proposed for blind source separation, but additive noise and reverberation must be considered ... [more] SIS2008-81
pp.55-59
SP, NLC 2008-12-09
10:00
Tokyo Waseda Univ. Two-channel input speech recognition using sparsness-based blind source separation
Kenta Nishiki, Yosuke Izumi (Univ. of Tokyo), Shinji Watanabe (NTT), Takuya Nishimoto, Nobutaka Ono, Shigeki Sagayama (Univ. of Tokyo) NLC2008-24 SP2008-79
This paper discusses a two-channel input speech recognition using a sparsness-based blind source separation. The target ... [more] NLC2008-24 SP2008-79
pp.1-6
SIS 2007-12-11
13:50
Hyogo   Impact Noise Suppression for Speech Signals by Using a Morphological Component Analysis with DFT
Hiroaki Hayashi, Makoto Nakashizuka, Youji Iiguni (Osaka Univ.) SIS2007-66
Morphological component analysis (MCA) is a signal separation method using sparse signal representations. For separation... [more] SIS2007-66
pp.47-52
 Results 21 - 40 of 50 [Previous]  /  [Next]  
Choose a download format for default settings. [NEW !!]
Text format pLaTeX format CSV format BibTeX format
Copyright and reproduction : All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)


[Return to Top Page]

[Return to IEICE Web Page]


The Institute of Electronics, Information and Communication Engineers (IEICE), Japan