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| Presentation | 2019-08-28 17:00 Speech Emotion Classification based on Multi-Label Emotion Existence Estimation Atsushi Ando, Ryo Masumura, Hosana Kamiyama, Satoshi Kobashikawa, Yushi Aono (NTT)  SP2019-16 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | This paper presents a novel speech emotion classification that addresses the ambiguous nature of emotions in speech. Most conventional methods assume there is only a single ground truth, the dominant emotion, though utterances can contain minor emotions. These mismatch yields performance degradation. In order to solve this problem, several methods that consider ambiguous emotions~(e.g.~soft-target training) have been proposed. Unfortunately, training them is difficult since they work by estimating the proportions of all emotions. The proposed method improves both frameworks by assessing the presence or absence of each emotion before specifying the dominant. We expect that it is much easier to estimate just presence/absence of emotions rather than trying to determine proportions of each, and the deliberate assessment of emotion existence information will help to estimate the proportion of each or dominant class more precisely. The proposed method employs two-step training. Multi-Label Emotion Existence~(MLEE) model is trained first to estimate whether each emotion is present or absent. Then, the dominant emotion recognition model with hard- or soft-target labels is trained by means of the intermediate outputs of the MLEE model. Experiments demonstrate that the proposed method outperforms both hard- or soft-target based conventional emotion recognition schemes. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | emotion recognition / multi-label classification / convolutional neural network (CNN) / spectrogram / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 188, SP2019-16, pp. 39-44, Aug. 2019. | |
| Paper # | SP2019-16 | |
| Date of Issue | 2019-08-21 (SP) | |
| 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 | SP2019-16 |
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| Conference Information | |
| Committee | SP |
| Conference Date | 2019-08-28 - 2019-08-28 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kyoto Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SP |
| Conference Code | 2019-08-SP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Speech Emotion Classification based on Multi-Label Emotion Existence Estimation |
| Sub Title (in English) | |
| Keyword(1) | emotion recognition |
| Keyword(2) | multi-label classification |
| Keyword(3) | convolutional neural network (CNN) |
| Keyword(4) | spectrogram |
| Keyword(5) | |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Atsushi Ando |
| 1st Author's Affiliation | Nippon Telegraph and Telephone Corporation (NTT) |
| 2nd Author's Name | Ryo Masumura |
| 2nd Author's Affiliation | Nippon Telegraph and Telephone Corporation (NTT) |
| 3rd Author's Name | Hosana Kamiyama |
| 3rd Author's Affiliation | Nippon Telegraph and Telephone Corporation (NTT) |
| 4th Author's Name | Satoshi Kobashikawa |
| 4th Author's Affiliation | Nippon Telegraph and Telephone Corporation (NTT) |
| 5th Author's Name | Yushi Aono |
| 5th Author's Affiliation | Nippon Telegraph and Telephone Corporation (NTT) |
| 6th Author's Name | |
| 6th Author's Affiliation | () |
| Speaker | Author-1 |
| Date Time | 2019-08-28 17:00:00 |
| Presentation Time | 25 minutes |
| Registration for | SP |
| Paper # | SP2019-16 |
| Volume (vol) | vol.119 |
| Number (no) | no.188 |
| Page | pp.39-44 |
| #Pages | 6 |
| Date of Issue | 2019-08-21 (SP) |
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