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- W2767030624 abstract "Major depressive disorder is a common mental disorder that affects almost 7% of the adult U.S. population. The 2017 Audio/Visual Emotion Challenge (AVEC) asks participants to build a model to predict depression levels based on the audio, video, and text of an interview ranging between 7-33 minutes. Since averaging features over the entire interview will lose most temporal information, how to discover, capture, and preserve useful temporal details for such a long interview are significant challenges. Therefore, we propose a novel topic modeling based approach to perform context-aware analysis of the recording. Our experiments show that the proposed approach outperforms context-unaware methods and the challenge baselines for all metrics." @default.
- W2767030624 created "2017-11-10" @default.
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- W2767030624 date "2017-10-23" @default.
- W2767030624 modified "2023-10-12" @default.
- W2767030624 title "Topic Modeling Based Multi-modal Depression Detection" @default.
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- W2767030624 doi "https://doi.org/10.1145/3133944.3133945" @default.
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