2018
NAACL
NAACL 2018
A Linguistically-Informed Fusion Approach for Multimodal Depression Detection
Abstract
AbstractAutomated depression detection is inherently a multimodal problem. Therefore, it is critical that researchers investigate fusion techniques for multimodal design. This paper presents the first-ever comprehensive study of fusion techniques for depression detection. In addition, we present novel linguistically-motivated fusion techniques, which we find outperform existing approaches.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning
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Hot Topic Early Bird
— multimodal fusion
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio