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Paper Abstract and Keywords
Presentation 2022-12-15 16:00
[Short Paper] An Intra- and Inter-Modality Transformer-based Fusion Model Using Multiemotional Audiovisual Features for Depression Prediction
Shiyu Teng, Shurong Chai, Jiaqing Liu (Ritsumeikan Univ.), Tateyama Tomoko (Fujita Health Univ.), Xinyin Huang (Soochow Univ.), Yen-wei Chen (Ritsumeikan Univ.) PRMU2022-42
Abstract (in Japanese) (See Japanese page) 
(in English) Depression is a prevalent mental ailment that causes many diseases all over the world. Identification of people with mental illness faces a challenge, as there is no difference between mentally ill people and normal people in physiology, and clinicians can only make a subjective diagnosis according to the relevant information of patients. Hence, it has become imperative to develop automated methods for audiovisual depression prediction. In this study, we proposed an intra- and inter-modality transformer-based fusion model to improve the depression level prediction accuracy. We evaluate our approach on the Chinese Soochow University depressive severity dataset and demonstrate that our method outperforms the existing method.
Keyword (in Japanese) (See Japanese page) 
(in English) Depression Prediction / Multi-Modalities / Fusion / Transformer / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 314, PRMU2022-42, pp. 54-56, Dec. 2022.
Paper # PRMU2022-42 
Date of Issue 2022-12-08 (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)
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Conference Information
Committee PRMU  
Conference Date 2022-12-15 - 2022-12-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Toyama International Conference Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2022-12-PRMU 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Intra- and Inter-Modality Transformer-based Fusion Model Using Multiemotional Audiovisual Features for Depression Prediction 
Sub Title (in English)  
Keyword(1) Depression Prediction  
Keyword(2) Multi-Modalities  
Keyword(3) Fusion  
Keyword(4) Transformer  
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1st Author's Name Shiyu Teng  
1st Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
2nd Author's Name Shurong Chai  
2nd Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
3rd Author's Name Jiaqing Liu  
3rd Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
4th Author's Name Tateyama Tomoko  
4th Author's Affiliation Fujita Health University (Fujita Health Univ.)
5th Author's Name Xinyin Huang  
5th Author's Affiliation Soochow University (Soochow Univ.)
6th Author's Name Yen-wei Chen  
6th Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
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Speaker Author-1 
Date Time 2022-12-15 16:00:00 
Presentation Time 10 minutes 
Registration for PRMU 
Paper # PRMU2022-42 
Volume (vol) vol.122 
Number (no) no.314 
Page pp.54-56 
#Pages 3 
Date of Issue 2022-12-08 (PRMU) 

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