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Paper Abstract and Keywords
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
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) 
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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
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 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 
Sub Title (in English)  
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 
Date of Issue 2021-02-25 (PRMU) 

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