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| Presentation | 2020-12-23 10:00 Acoustic features of a Japanese speech corpus for emotion(al) intensity estimation Megumi Kawase, Minoru Nakayama (Tokyo Tech)  HIP2020-64 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | ecently, there have been many studies on emotion estimation from non-linguistic speech data, but few studies on emotion intensity.However, failure to read this emotional intensity can lead to errors in the responses humans and machines should take when communicating with each other. In this paper, we developed three models for emotion intensity estimation using deep learning, and examined the accuracy of emotion intensity estimation for Japanese speech corpus, which resulted in 52.4% accuracy of emotion intensity estimation. We also investigated the correlations between acoustic features and analyzed the properties of acoustic features in order to improve the estimation accuracy, and found that the differentiation of gammatone frequency cepstral coefficients was significantly different between intensities. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | speech / emotion / intensity / acoustic features / deep learning / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 306, HIP2020-64, pp. 55-60, Dec. 2020. | |
| Paper # | HIP2020-64 | |
| Date of Issue | 2020-12-15 (HIP) | |
| ISSN | 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) | |
| Download PDF | HIP2020-64 |
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| Conference Information | |
| Committee | HIP |
| Conference Date | 2020-12-22 - 2020-12-23 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | HIP |
| Conference Code | 2020-12-HIP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Acoustic features of a Japanese speech corpus for emotion(al) intensity estimation |
| Sub Title (in English) | |
| Keyword(1) | speech |
| Keyword(2) | emotion |
| Keyword(3) | intensity |
| Keyword(4) | acoustic features |
| Keyword(5) | deep learning |
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| 1st Author's Name | Megumi Kawase |
| 1st Author's Affiliation | Tokyo Institute of Technology (Tokyo Tech) |
| 2nd Author's Name | Minoru Nakayama |
| 2nd Author's Affiliation | Tokyo Institute of Technology (Tokyo Tech) |
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| Speaker | Author-1 |
| Date Time | 2020-12-23 10:00:00 |
| Presentation Time | 30 minutes |
| Registration for | HIP |
| Paper # | HIP2020-64 |
| Volume (vol) | vol.120 |
| Number (no) | no.306 |
| Page | pp.55-60 |
| #Pages | 6 |
| Date of Issue | 2020-12-15 (HIP) |
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