ArticleProceedings of the ... ACM International Conference on Multimodal Interaction. ICMI (Conference)2021
Human-Guided Modality Informativeness for Affective States.
Article in Proceedings of the ... ACM International Conference on Multimodal Interaction. ICMI (Conference), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- SMURF: Statistical Modality Uniqueness and Redundancy Factorization.Proceedings of the ... ACM International Conference on Multimodal Interaction. ICMI (Conference) · 2024Article
- SHAP-based Prediction of Mother's History of Depression to Understand the Influence on Child Behavior.Proceedings of the ... ACM International Conference on Multimodal Interaction. ICMI (Conference) · 2023Article
- Beyond Additive Fusion: Learning Non-Additive Multimodal Interactions.Findings of ACL. EMNLP. Conference on Empirical Methods in Natural Language Processing · 2022Article
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Authors and funding
5 authors.
Funding
Abstract
This paper studies the hypothesis that not all modalities are always needed to predict affective states. We explore this hypothesis in the context of recognizing three affective states that have shown a relation to a future onset of depression: positive, aggressive, and dysphoric. In particular, we investigate three important modalities for face-to-face conversations: vision, language, and acoustic modality. We first perform a human study to better understand which subset of modalities people find informative, when recognizing three affective states. As a second contribution, we explore how these human annotations can guide automatic affect recognition systems to be more interpretable while not degrading their predictive performance. Our studies show that humans can reliably annotate modality informativeness. Further, we observe that guided models significantly improve interpretability, i.e., they attend to modalities similarly to how humans rate the modality informativeness, while at the same time showing a slight increase in predictive performance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.