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 |