Two Birds With One Stone: Knowledge-Embedded Temporal Convolutional Transformer for Depression Detection and Emotion Recognition
文献类型：期刊论文
| 作者 | Zheng, Wenbo4,5; Yan, Lan2,3 ; Wang, Fei-Yue1
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| 刊名 | IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
 |
| 出版日期 | 2023-10-01 |
| 卷号 | 14期号:4页码:2595-2613 |
| 关键词 | Multimodal depression detection multimodal emotion recognition transformer knowledge embedding joint learning |
| ISSN号 | 1949-3045 |
| DOI | 10.1109/TAFFC.2023.3282704 |
| 通讯作者 | Zheng, Wenbo(zwb2022@whut.edu.cn) |
| 英文摘要 | Depression is a critical problem in modern society that affects an estimated 350 million people worldwide, causing feelings of sadness and a lack of interest and pleasure. Emotional disorders are gaining interest and are closely entwined with depression, because one contributes to an understanding of the other. Despite the achievements in the two separate tasks of emotion recognition and depression detection, there has not been much prior effort to build a unified model that can connect these two tasks with different modalities, including multimedia (text, audio, and video) and unobtrusive physiological signals (e.g., electroencephalography). We propose a novel temporal convolutional transformer with knowledge embedding to address the joint task of depression detection and emotion recognition. This approach not only learns multimodal embeddings across domains via the temporal convolutional transformer but also exploits special-domain knowledge from medical knowledge graphs to improve the performance of detection and recognition. It is essential that the features learned by our method can be perceived as a priori and are suitable for increasing the performance of other related tasks. Our method illustrates the case of "two birds with one stone" in the sense that two or more tasks can be efficiently handled with our unique model, which captures effective features. Experimental results on ten real-world datasets show that the proposed approach significantly outperforms other state-of-the-art approaches. On the other hand, experiments in which our methodology is applied to other reasoning tasks show that our approach effectively supports model reasoning related to emotion and improves its performance. |
| WOS关键词 | SENTIMENT ANALYSIS ; REPRESENTATION ; INTELLIGENCE |
| 资助项目 | Hainan Provincial Natural Science Foundation of China |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001124163900056 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | Hainan Provincial Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/55658]  |
| 专题 | 多模态人工智能系统全国重点实验室 |
| 通讯作者 | Zheng, Wenbo |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Natl Supercomp Ctr, Changsha 410082, Hunan, Peoples R China 3.Hunan Univ, Coll Informat Sci & Engn, Changsha 410012, Peoples R China 4.Wuhan Univ Technol, Sanya Sci & Educ Innovat Pk, Sanya 572000, Peoples R China 5.Wuhan Univ Technol, Sch Comp Sci & Artificial Intelligence, Wuhan 430070, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zheng, Wenbo,Yan, Lan,Wang, Fei-Yue. Two Birds With One Stone: Knowledge-Embedded Temporal Convolutional Transformer for Depression Detection and Emotion Recognition[J]. IEEE TRANSACTIONS ON AFFECTIVE COMPUTING,2023,14(4):2595-2613. |
| APA | Zheng, Wenbo,Yan, Lan,&Wang, Fei-Yue.(2023).Two Birds With One Stone: Knowledge-Embedded Temporal Convolutional Transformer for Depression Detection and Emotion Recognition.IEEE TRANSACTIONS ON AFFECTIVE COMPUTING,14(4),2595-2613. |
| MLA | Zheng, Wenbo,et al."Two Birds With One Stone: Knowledge-Embedded Temporal Convolutional Transformer for Depression Detection and Emotion Recognition".IEEE TRANSACTIONS ON AFFECTIVE COMPUTING 14.4(2023):2595-2613. |
入库方式： OAI收割
来源：自动化研究所
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