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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.08332 |
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| _version_ | 1866929536111738880 |
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| author | Carrasco, Miguel Gonzalez-Martin, Cesar Navajas-Torrente, Sonia Dastres, Raul |
| author_facet | Carrasco, Miguel Gonzalez-Martin, Cesar Navajas-Torrente, Sonia Dastres, Raul |
| contents | Images are capable of conveying emotions, but emotional experience is highly subjective. Advances in artificial intelligence have enabled the generation of images based on emotional descriptions. However, the level of agreement between the generative images and human emotional responses has not yet been evaluated. To address this, 20 artistic landscapes were generated using StyleGAN2-ADA. Four variants evoking positive emotions (contentment, amusement) and negative emotions (fear, sadness) were created for each image, resulting in 80 pictures. An online questionnaire was designed using this material, in which 61 observers classified the generated images. Statistical analyses were performed on the collected data to determine the level of agreement among participants, between the observer's responses, and the AI-generated emotions. A generally good level of agreement was found, with better results for negative emotions. However, the study confirms the subjectivity inherent in emotional evaluation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_08332 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Level of agreement between emotions generated by Artificial Intelligence and human evaluation: a methodological proposal Carrasco, Miguel Gonzalez-Martin, Cesar Navajas-Torrente, Sonia Dastres, Raul Computer Vision and Pattern Recognition Artificial Intelligence Images are capable of conveying emotions, but emotional experience is highly subjective. Advances in artificial intelligence have enabled the generation of images based on emotional descriptions. However, the level of agreement between the generative images and human emotional responses has not yet been evaluated. To address this, 20 artistic landscapes were generated using StyleGAN2-ADA. Four variants evoking positive emotions (contentment, amusement) and negative emotions (fear, sadness) were created for each image, resulting in 80 pictures. An online questionnaire was designed using this material, in which 61 observers classified the generated images. Statistical analyses were performed on the collected data to determine the level of agreement among participants, between the observer's responses, and the AI-generated emotions. A generally good level of agreement was found, with better results for negative emotions. However, the study confirms the subjectivity inherent in emotional evaluation. |
| title | Level of agreement between emotions generated by Artificial Intelligence and human evaluation: a methodological proposal |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2410.08332 |