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Paper Abstract and Keywords
Presentation
On Noise Robustness of Feature Expressing Temporal Variation for Word Speech Recognition
Tetsuo Funada, Megumi Umeno, Hideyuki Nomura (Kanazawa Univ.) SP2007-33
Abstract (in Japanese) (See Japanese page) 
(in English) In previous paper, we proposed a feature FTTSS (Fourier Transform of Ternarized Spectral Slope) based on power spectral derivatives with regard to frequency to develop a robust word recognition system under noisy environments. Generally, word recognition using HMM is improved by adding features that express temporal variations, such as MFCC or FTTSS, because HMM can deal with only piecewise stationary signals. Actually, we have examined effectiveness of using FTTSS in word recognition. In computing Δ-quantity, average temporal slope of the parameter in several frames is used after transform- ing spectral pattern to spectral parameter. On the other hand, considering the frequency analysis in cochlear and existence of neurons fired by detecting peak frequency of spectrum going up or down in auditory inferior colliculus, it is supposed that fea- tures showing raw temporal variations of power spectrum are effective in speech recognition. In this research, we propose a new feature FTTTS (Fourier Transform of Ternarized Temporal Slope) instead of ΔFTTSS. The FTTTS is defined by Fourier Transform along frequency of smoothed ternarized temporal variations. Experimentally, we have confirmed noise robustness of the proposed feature FTTTS as compared with FTTSS.
Keyword (in Japanese) (See Japanese page) 
(in English) Speech Recognition / Noise Robustness / Temporal Feature / / / / /  
Reference Info. IEICE Tech. Rep., vol. 107, no. 165, SP2007-33, pp. 55-60, July 2007.
Paper # SP2007-33 
Date of Issue  
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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)
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Conference Information
Committee SP  
Conference Date 2007-07-26 - 2007-07-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Toyama Prefectural University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Speech Production, Speech Perception, Hearing and Speech, etc. 
Paper Information
Registration To SP 
Conference Code 2007-07-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) On Noise Robustness of Feature Expressing Temporal Variation for Word Speech Recognition 
Sub Title (in English)  
Keyword(1) Speech Recognition  
Keyword(2) Noise Robustness  
Keyword(3) Temporal Feature  
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1st Author's Name Tetsuo Funada  
1st Author's Affiliation Kanazawa University (Kanazawa Univ.)
2nd Author's Name Megumi Umeno  
2nd Author's Affiliation Kanazawa University (Kanazawa Univ.)
3rd Author's Name Hideyuki Nomura  
3rd Author's Affiliation Kanazawa University (Kanazawa Univ.)
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Speaker Author-1 
Date Time  
Presentation Time minutes 
Registration for SP 
Paper # SP2007-33 
Volume (vol) vol.107 
Number (no) no.165 
Page pp.55-60 
#Pages 6 
Date of Issue  

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