Abstract

The study of multimodality is comparatively less developed for Affective interfaces than for their traditional counterparts. However, one condition for the successful development of Affective interface technologies is the development of frameworks for the real-time multimodal fusion. In this paper, we describe an approach to multimodal affective fusion, which relies on a dimensional model, Pleasure-Arousal-Dominance (PAD) to support the fusion of affective modalities, each input modality being represented as a PAD vector. We describe how this model supports both affective content fusion and temporal fusion within a unified approach. We report results from early user studies which confirm the existence of a correlation between measured affective input and user temperament scores.

Keywords:
Multimodality Modalities Modality (human–computer interaction) Affective computing Arousal Fusion Computer science Pleasure Sensor fusion Multimodal therapy Temperament Exploit Artificial intelligence Dominance (genetics) Cognitive psychology Human–computer interaction Psychology Psychotherapist Social psychology Personality

Metrics

27
Cited By
5.34
FWCI (Field Weighted Citation Impact)
53
Refs
0.97
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Speech and dialogue systems
Physical Sciences →  Computer Science →  Artificial Intelligence
Emotion and Mood Recognition
Social Sciences →  Psychology →  Experimental and Cognitive Psychology
Social Robot Interaction and HRI
Social Sciences →  Psychology →  Social Psychology

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