Modelling Emotions is an Elusive Pursuit in Affective Computing
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866913046910205952 |
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| author | Larsen, Anders Rolighed Das, Sneha Lønfeldt, Nicole Nadine Petcu, Paula Clemmensen, Line |
| author_facet | Larsen, Anders Rolighed Das, Sneha Lønfeldt, Nicole Nadine Petcu, Paula Clemmensen, Line |
| contents | Affective computing - combining sensor technology, machine learning, and psychology - have been studied for over three decades and is employed in AI-powered technologies to enhance emotional awareness in AI systems, and detect symptoms of mental health disorders such as anxiety and depression. However, the uncertainty in such systems remains high, and the application areas are limited by categorical definitions of emotions and emotional concepts. This paper argues that categorical emotion labels obscure emotional nuance in affective computing, and therefore continuous dimensional definitions are needed to advance the field, increase application usefulness, and lower uncertainties. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_23017 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Modelling Emotions is an Elusive Pursuit in Affective Computing Larsen, Anders Rolighed Das, Sneha Lønfeldt, Nicole Nadine Petcu, Paula Clemmensen, Line Audio and Speech Processing Affective computing - combining sensor technology, machine learning, and psychology - have been studied for over three decades and is employed in AI-powered technologies to enhance emotional awareness in AI systems, and detect symptoms of mental health disorders such as anxiety and depression. However, the uncertainty in such systems remains high, and the application areas are limited by categorical definitions of emotions and emotional concepts. This paper argues that categorical emotion labels obscure emotional nuance in affective computing, and therefore continuous dimensional definitions are needed to advance the field, increase application usefulness, and lower uncertainties. |
| title | Modelling Emotions is an Elusive Pursuit in Affective Computing |
| topic | Audio and Speech Processing |
| url | https://arxiv.org/abs/2603.23017 |