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arXiv · 2406.14908

Can we say a cat is a cat? Understanding the challenges in annotating physiological signal-based emotion data

Pragya Singh·Mohan Kumar·Pushpendra Singh
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Abstract

Artificial Intelligence (AI) algorithms, trained on emotion data extracted from physiological signals, provide a promising approach to monitoring emotions, affect, and mental well-being. However, the field encounters challenges because there is a lack of effective methods for collecting high-quality data in everyday settings that genuinely reflect changes in emotion or affect. This paper presents a position discussion on the current technique of annotating physiological signal-based emotion data. Our discourse underscores the importance of adopting a nuanced understanding of annotation processes, paving the way for a more insightful exploration of the intricate relationship between physiological signals and human emotions.

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Pragya Singh, Mohan Kumar, Pushpendra Singh. 2024-06-21. Can we say a cat is a cat? Understanding the challenges in annotating physiological signal-based emotion data. https://arxiv.org/abs/2406.14908

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