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Paper Abstract and Keywords
Presentation 2019-06-10 10:30
Impression Prediction of Oral Presentation Using LSTM with Dot-product Attention Mechanism
Shengzhou Yi, Xueting Wang, Toshihiko Yamasaki (UTokyo) MVE2019-1
Abstract (in Japanese) (See Japanese page) 
(in English) For automatically evaluating oral presentation, we propose an end-to-end system to predict audience’s impression on speech video. Our framework is a multimodal neural network including two Long Short-Term Memory (LSTM) with dot-product attention mechanism to learn linguistic feature and acoustic feature respectively for our classification task, as well as a hidden network to consider the correlation between different types of feature representations for model-level fusion. We utilize 2,445 videos with official captions and users’ ratings from TED Talks. The experiment result shows the good performance of our proposal can recognize audience’s 14 types of impression with the average accuracy of 85.3%.
Keyword (in Japanese) (See Japanese page) 
(in English) Presentation Analysis / Multimodal Network / End-to-End System / TED Talks / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 75, MVE2019-1, pp. 1-6, June 2019.
Paper # MVE2019-1 
Date of Issue 2019-06-03 (MVE) 
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. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee MVE ITE-HI ITE-SIP  
Conference Date 2019-06-10 - 2019-06-11 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MVE 
Conference Code 2019-06-MVE-HI-SIP 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Impression Prediction of Oral Presentation Using LSTM with Dot-product Attention Mechanism 
Sub Title (in English)  
Keyword(1) Presentation Analysis  
Keyword(2) Multimodal Network  
Keyword(3) End-to-End System  
Keyword(4) TED Talks  
1st Author's Name Shengzhou Yi  
1st Author's Affiliation The University of Tokyo (UTokyo)
2nd Author's Name Xueting Wang  
2nd Author's Affiliation The University of Tokyo (UTokyo)
3rd Author's Name Toshihiko Yamasaki  
3rd Author's Affiliation The University of Tokyo (UTokyo)
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Speaker Author-1 
Date Time 2019-06-10 10:30:00 
Presentation Time 30 minutes 
Registration for MVE 
Paper # MVE2019-1 
Volume (vol) vol.119 
Number (no) no.75 
Page pp.1-6 
Date of Issue 2019-06-03 (MVE) 

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