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#affective-computing

3 curated events
papersTODAY 04:00 UTC

Compact ML Models Classify Affective Touch in Soft Interactive Companion

Researchers describe an end-to-end pipeline for recognizing touch gestures on a plush companion robot, whose soft body and spread-out tactile sensors complicate reliable detection. The work covers the design of small machine-learning models along with embedded validation to confirm they run effectively on the device itself. The abstract is truncated, so full details of the methods and results are not yet available.

papersTODAY 04:00 UTC

Spook the Machine: Gamified Study Explores Human Imagination of Machine Fear

Researchers built a gamified platform called Spook the Machine in which participants craft and interact with AI characters that display fear. The study examines whether people respond differently depending on how a machine expresses fear, and what those reactions suggest for designing affective human-AI interaction. It is an arXiv preprint focused on emotion-oriented AI design.

papersSEP 10 04:00 UTC

Researchers propose relational paradigm for affective computing in vocal interactions

A new arXiv paper argues that affective computing's dominant approach, which assigns discrete emotion labels or arousal/valence scores to individual speakers, is inadequate for understanding emotional life as it happens between people. The authors instead build on the ideas of affective resonance and vitality affects to model vocal exchanges as dynamic, shared interaction fields. The work reframes emotion recognition as a relational process rather than the classification of isolated internal states.