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 |
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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MVE2019-1 |
Conference Information |
Committee |
MVE ITE-HI ITE-SIP |
Conference Date |
2019-06-10 - 2019-06-11 |
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(See Japanese page) |
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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 |
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Keyword(1) |
Presentation Analysis |
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Multimodal Network |
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End-to-End System |
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TED Talks |
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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 |
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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 |
#Pages |
6 |
Date of Issue |
2019-06-03 (MVE) |
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