| 講演抄録/キーワード |
| 講演名 |
2024-05-16 15:40
ウェブ面接データを用いたうつ病の検出 ○ラム チューク ヘイ・ナー ナタニア・篠田浩一(東工大)・北沢桃子・貝瀬有里子(慶大)・高木俊輔・杉原玄一(東京医科歯科大)・岸本泰士郎(慶大) PRMU2024-7 |
| 抄録 |
(和) |
(まだ登録されていません) |
| (英) |
This paper presents a method for integrating speech, text, and video modalities for multimodal depression detection. Our work leverages shorter utterances to enhance depression detection accuracy, rather than relying on traditional long-term approaches. We introduce the COI-NEXT dataset, comprising authentic clinical interviews conducted through Zoom. Our experiments show that video modalities, particularly when using shorter utterances, lead to improved accuracy for depression detection in patients. Despite limitations due to data scarcity, this work offers valuable insights into multimodal depression detection, emphasizing the significance of multimodal integration in mental health research. |
| キーワード |
(和) |
/ / / / / / / |
| (英) |
Depression Detection / Web Interview / Multimodal Learning / / / / / |
| 文献情報 |
信学技報, vol. 124, no. 23, PRMU2024-7, pp. 36-40, 2024年5月. |
| 資料番号 |
PRMU2024-7 |
| 発行日 |
2024-05-08 (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 |
PRMU2024-7 |