Can we say a cat is a cat? Understanding the challenges in annotating physiological signal-based emotion data
<|reference_start|>Can we say a cat is a cat? Understanding the challenges in annotating physiological signal-based emotion data: 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.<|reference_end|>
@article{singh2024can,
    title={Can we say a cat is a cat? Understanding the challenges in annotating
  physiological signal-based emotion data},
    author={Pragya Singh, Mohan Kumar, Pushpendra Singh},
    journal={arXiv preprint arXiv:2406.14908},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.14908},
    primaryClass={cs.HC}
}