講演抄録/キーワード |
講演名 |
2022-12-15 16:00
[ショートペーパー]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 |
抄録 |
(和) |
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. |
(英) |
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. |
キーワード |
(和) |
Depression Prediction / Multi-Modalities / Fusion / Transformer / / / / |
(英) |
Depression Prediction / Multi-Modalities / Fusion / Transformer / / / / |
文献情報 |
信学技報, vol. 122, no. 314, PRMU2022-42, pp. 54-56, 2022年12月. |
資料番号 |
PRMU2022-42 |
発行日 |
2022-12-08 (PRMU) |
ISSN |
Online edition: ISSN 2432-6380 |
著作権に ついて |
技術研究報告に掲載された論文の著作権は電子情報通信学会に帰属します.(許諾番号:10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
PDFダウンロード |
PRMU2022-42 |