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| Presentation | 2021-03-04 16:50 [Short Paper] A CNN-Transformer-Based Network for Depression Recognition Liu Jiaqing (Ritsumei), Huang Yue, Huang Xinren (Soochow), Tateyama Tomoko (Shiga University), Iwamoto Yutaro, Chen Yanwei (Ritsumei)  PRMU2020-83 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Depressive symptoms are a massive problem in this stressful modern society. Early screening of depressive symptoms helps to reduce the number and intensity of their depressive episodes. Automatic detection of depressive symptoms from audio cues has gained increasing interest in recent years. Transformer-based neural networks represent a successful self-attention mechanism that achieves state-of-the-art results in language understanding and sequence modeling. However, their application to visual data and, in particular, to the depressive severity detection task has not yet been deeply investigated. In this paper, we propose a transformer-based architecture for the depressive task. The temporal feature analysis using transformer computed after the feature extraction performed by DensNet. Our experimental results show that the proposed method can achieve CCC of 0.34 when using the validation set and 0.24 when using the test set, significantly outperforming the baseline method score CCC of 0.165. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | / / / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 409, PRMU2020-83, pp. 83-85, March 2021. | |
| Paper # | PRMU2020-83 | |
| Date of Issue | 2021-02-25 (PRMU) | |
| 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 | PRMU2020-83 |
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| Conference Information | |
| Committee | PRMU IPSJ-CVIM |
| Conference Date | 2021-03-04 - 2021-03-05 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Computer Vision and Pattern Recognition for specific environment |
| Paper Information | |
| Registration To | PRMU |
| Conference Code | 2021-03-PRMU-CVIM |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A CNN-Transformer-Based Network for Depression Recognition |
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| 1st Author's Name | Liu Jiaqing |
| 1st Author's Affiliation | Ritsumeikan University (Ritsumei) |
| 2nd Author's Name | Huang Yue |
| 2nd Author's Affiliation | Soochow University (Soochow) |
| 3rd Author's Name | Huang Xinren |
| 3rd Author's Affiliation | Soochow University (Soochow) |
| 4th Author's Name | Tateyama Tomoko |
| 4th Author's Affiliation | Shiga University (Shiga University) |
| 5th Author's Name | Iwamoto Yutaro |
| 5th Author's Affiliation | Ritsumeikan University (Ritsumei) |
| 6th Author's Name | Chen Yanwei |
| 6th Author's Affiliation | Ritsumeikan University (Ritsumei) |
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| Speaker | Author-1 |
| Date Time | 2021-03-04 16:50:00 |
| Presentation Time | 10 minutes |
| Registration for | PRMU |
| Paper # | PRMU2020-83 |
| Volume (vol) | vol.120 |
| Number (no) | no.409 |
| Page | pp.83-85 |
| #Pages | 3 |
| Date of Issue | 2021-02-25 (PRMU) |
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