TY - JOUR
T1 - Level of Agreement between Emotions Generated by Artificial Intelligence and Human Evaluation
T2 - A Methodological Proposal
AU - Carrasco, Miguel
AU - González-Martín, César
AU - Navajas-Torrente, Sonia
AU - Dastres, Raúl
N1 - Publisher Copyright:
© 2024 by the authors.
PY - 2024/10
Y1 - 2024/10
N2 - 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. In order to address this, 20 artistic landscapes were generated using StyleGAN2-ADA. Four variants evoking positive emotions (contentment and amusement) and negative emotions (fear and 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 observers’ responses and the generated emotions by AI. A generally good level of agreement was found, with better results for negative emotions. However, the study confirms the subjectivity inherent in emotional evaluation.
AB - 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. In order to address this, 20 artistic landscapes were generated using StyleGAN2-ADA. Four variants evoking positive emotions (contentment and amusement) and negative emotions (fear and 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 observers’ responses and the generated emotions by AI. A generally good level of agreement was found, with better results for negative emotions. However, the study confirms the subjectivity inherent in emotional evaluation.
KW - agreement
KW - emotion
KW - generative neural networks
UR - http://www.scopus.com/inward/record.url?scp=85207676140&partnerID=8YFLogxK
U2 - 10.3390/electronics13204014
DO - 10.3390/electronics13204014
M3 - Article
AN - SCOPUS:85207676140
SN - 2079-9292
VL - 13
JO - Electronics (Switzerland)
JF - Electronics (Switzerland)
IS - 20
M1 - 4014
ER -