Kazumasa YAMAMOTO

J-GLOBAL         Last updated: Oct 3, 2018 at 10:01
 
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Name
Kazumasa YAMAMOTO
Affiliation
Chubu University
Section
Department of Computer Science
Job title
Assistant Professor
Degree
Doctor of Engineering(Toyohashi University of Technology)

Profile

I am a reseacher of speech information processing, especially robust speech recognition.

Academic & Professional Experience

 
Apr 2017
 - 
Today
Associate Professor, Department of Computer Science, Chubu University
 
Apr 2013
 - 
Mar 2014
Associate Professor, Department of Information and Computer Engineering, Toyota National College of Technology
 
Mar 2013
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Mar 2017
Associate Professor, Department of Computer Science and Engineering, Toyohashi University of Technology
 
Feb 2012
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Sep 2012
Visiting Researcher, Department of Electrical and Computer Engineering, Carnegie Mellon University
 
Apr 2010
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Feb 2013
Assistant Professor, Department of Computer Science and Engineering, Toyohashi University of Technology
 
Apr 2007
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Mar 2010
Assistant Professor, Department of Information and Computer Sciences, Toyohashi University of Technology
 
Apr 2000
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Mar 2007
Research Associate, Department of Electrical and Elerctronic Engineering, Shinshu University
 

Published Papers

 
KITAOKA Norihide, YANO Hirotoshi, SUGIMOTO Natsuki, YAMAMOTO Kazumasa, NAKAGAWA Seiichi
The IEICE transactions on information and systems (Japanese edetion)   95(4) 982-994   Apr 2012
NAKANO Alberto Yoshihiro, NAKAGAWA Seiichi, YAMAMOTO Kazumasa
IEICE Transactions on Information and Systems   E93-D(9) 2451-2462   Sep 2010
In this work, spatial information consisting of the position and orientation angle of an acoustic source is estimated by an artificial neural network (ANN). The estimated position of a speaker in an enclosed space is used to refine the estimated t...
WANG Longbiao, MINAMI Kazue, YAMAMOTO Kazumasa, NAKAGAWA Seiichi
IEICE Transactions on Information and Systems   E93-D(9) 2397-2406   Sep 2010
In this paper, we investigate the effectiveness of phase for speaker recognition in noisy conditions and combine the phase information with mel-frequency cepstral coefficients (MFCCs). To date, almost speaker recognition methods are based on MFCCs...
Yasuhisa Fujii, Kazumasa Yamamoto, Norihide Kitaoka, Seiichi Nakagawa
IPSJ Journal   51(3) 1094-1106   Mar 2010
This paper describes summarization methods based on important sentence extraction for the summarization of class-room lecture. First, we compare two summarization techniques; a Maximal Marginal Relevance and a feature-based method which uses a Sup...
Nakano Alberto Yoshihiro, Nakagawa Seiichi, Yamamoto Kazumasa
Acoustical Science and Technology   31(5) 309-319   2010
In this work, the perception of the position and orientation of a directional acoustic source in a real enclosed environment by blindfolded listeners is investigated and compared with a method that automatically estimates the position and orientat...

Misc

 
IWAMI KEISUKE, YAMAMOTO KAZUMASA, NAKAGAWA SEIICHI
IEICE technical report. Speech   111(365) 25-32   Dec 2011
We can find the information with an existing textual search engine if the target data consist of text information such as news and newspaper, but efficient spoken term detection (STD) method is not currently the established, because spoken documen...
IWAMI KEISUKE, YAMAMOTO KAZUMASA, NAKAGAWA SEIICHI
IEICE technical report. Natural language understanding and models of communication   111(364) 25-32   Dec 2011
We can find the information with an existing textual search engine if the target data consist of text information such as news and newspaper, but efficient spoken term detection (STD) method is not currently the established, because spoken documen...
NAKANO Shoichi, YAMAMOTO Kazumasa, NAKAGAWA Seiichi
IEICE technical report. Speech   111(97) 23-28   Jun 2011
For speech recognition in the presence of noise, it is necessary to reduce the effect of the noise. The spectral subtraction and Wiener filter based methods are general techniques for noise removal. Although these methods are valid for stationary ...
Yasuhisa Fujii, Kazumasa Yamamoto, Seiichi Nakagawa
IPSJ SIG Notes   2011(13) 1-6   Jan 2011
We have investigated automatic speech recognition using Hidden Conditional Neural Fields(HCNF). In this paper, we propose a new objective function, Hidden Boosted MMI(HB-MMI), which can consider the number of errors in training data even if the co...
Yasuhisa Fujii, Kazumasa Yamamoto, Seiichi Nakagawa
IPSJ SIG Notes   2010(1) 1-6   Oct 2010
Recently, there has been increasing attention in automatic speech recognition using discriminative models. Especially, Hidden Conditional Random Fields(HCRF) is a natural extension of traditional HMM and therefore very promising. However, because ...
Keisuke Iwami, Yasuhisa Fujii, Kazumasa Yamamoto, Seiichi Nakagawa
IPSJ SIG Notes   2010(3) 1-6   Oct 2010
We can find the information with an existing textual search engine if the target data consist of text information such as news and newspaper, but efficient spoken document retrieval (SDR) method is not currently the established, because spoken doc...
Satoshi Tamura, Chiyomi Miyajima, Norihide Kitaoka, Kazuya Takeda, Takeshi Yamada, Tetsuya Takiguchi, Satoru Tsuge, Kazumasa Yamamoto, Takanobu Nishiura, Masato Nakayama, Yuki Denda, Masakiyo Fujimoto, Shigeki Matsuda, Tetsuji Ogawa, Shingo Kuroiwa, Satoshi Nakamura
IPSJ SIG Notes   2010(7) 1-6   Jul 2010
This paper introduces an evaluation framework for multimodal speech recognition: CENSREC-1-AV. The corpus CENSREC-1-AV provides an audiovisual speech database and a baseline system of multimodal speech recognition. Speech signals were recorded in ...
YAMAMOTO Kazumasa, SUEYOSHI Eiichi, NAKAGAWA Seiichi
IEICE technical report. Speech   110(143) 31-36   Jul 2010
Current speech recognition systems use mainly amplitude spectrum-based features such as MFFC for acoustic feature parameters, while discarding phase spectral information. The results of perceptual experiments, however, suggested that phase spectra...
Proceedings of the Spoken Document Processing Workshop   3(0) 133-138   Feb 2009

Research Grants & Projects

 
Ministry of Education, Culture, Sports, Science and Technology: Grants-in-Aid for Scientific Research(基盤研究(B))
Project Year: 2007 - 2009    Investigator(s): Kazuya TAKEDA
For distorted speech recognition under the real world, we conducted below : (1) development of distorted speech corpora named CENSREC and distribution of them in public ; (2) accurate recognition performance prediction for additively/convolutional...
Ministry of Education, Culture, Sports, Science and Technology: Grants-in-Aid for Scientific Research(若手研究(B))
Project Year: 2006 - 2008    Investigator(s): Kazumasa YAMAMOTO
Ministry of Education, Culture, Sports, Science and Technology: Grants-in-Aid for Scientific Research(基盤研究(C))
Project Year: 2003 - 2004    Investigator(s): Hiroshi MATSUMOTO
Firstly, we proposed a forward masking of Mel-LPC based spectrum on the generalized logarithmic scale. Besides, the variance normalization and a mashing control with the estimated SNR are examined for improving noise robustness.The experimental re...
Ministry of Education, Culture, Sports, Science and Technology: Grants-in-Aid for Scientific Research(基盤研究(C))
Project Year: 2000 - 2001    Investigator(s): Hiroshi MATSUMOTO
( 1 ) A Study on Robust Acoustic Parameters for Hands-free speech recognitionIn hands-free speech recognition, the variation of additive and convolutional noises due to the variable distance between speaker and microphone as well as reverberation ...