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Paper Abstract and Keywords
Presentation 2019-08-09 10:30
Study on Robust Method for Blindly Estimating Speech Transmission Index using Convolutional Neural Network with Temporal Amplitude Envelope
Suradej Doungpummet (JAIST), Jessada Karunjana (NASDA), Waree Kongprawechnon (SIIT), Masashi Unoki (JAIST) EA2019-30
Abstract (in Japanese) (See Japanese page) 
(in English) We have developed a robust scheme for blindly estimating speech transmission index (STI) in noisy reverberant environments based on a convolutional neural network (CNN) with temporal amplitude envelope feature. A method for estimating STI from an observed speech signal is required to predict the speech intelligibility in a sound field where people cannot be excluded. However, there is a significant accuracy reduction of an existing method based on the modulation transfer function due to the mismatch between the models and some real environments. To maintain an appropriate accuracy in general conditions, the robust scheme that the CNN is trained from entire temporal amplitude envelopes of speech signals with multiple noise types and reverberation conditions along with
their associated STIs has been introduced. Simulations were carried out to evaluate the proposed scheme under realistic noisy reverberant conditions. The results showed that the proposed scheme provides high accuracy (i.e., the average root-mean-square error of 0.12 and the correlation of 0.86) under various noise and reverberation conditions.
These results suggest that the proposed scheme can robustly estimate STIs in real noisy reverberant environments.
Keyword (in Japanese) (See Japanese page) 
(in English) Speech transmission index / room impulse response / modulation transfer function / temporal amplitude envelope / convolutional neural network / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 163, EA2019-30, pp. 47-52, Aug. 2019.
Paper # EA2019-30 
Date of Issue 2019-08-01 (EA) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF EA2019-30

Conference Information
Committee EA ASJ-H  
Conference Date 2019-08-08 - 2019-08-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Engineering/Electro Acoustics, Psychological and Physiological Acoustics, and Related Topics 
Paper Information
Registration To EA 
Conference Code 2019-08-EA-H 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study on Robust Method for Blindly Estimating Speech Transmission Index using Convolutional Neural Network with Temporal Amplitude Envelope 
Sub Title (in English)  
Keyword(1) Speech transmission index  
Keyword(2) room impulse response  
Keyword(3) modulation transfer function  
Keyword(4) temporal amplitude envelope  
Keyword(5) convolutional neural network  
1st Author's Name Suradej Doungpummet  
1st Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
2nd Author's Name Jessada Karunjana  
2nd Author's Affiliation National Science and Technology Development Agency (NASDA)
3rd Author's Name Waree Kongprawechnon  
3rd Author's Affiliation Sirindhorn International Institute of Technology (SIIT)
4th Author's Name Masashi Unoki  
4th Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
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Date Time 2019-08-09 10:30:00 
Presentation Time 30 
Registration for EA 
Paper # IEICE-EA2019-30 
Volume (vol) IEICE-119 
Number (no) no.163 
Page pp.47-52 
#Pages IEICE-6 
Date of Issue IEICE-EA-2019-08-01 

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