6 papers
Using hierarchical statistical learning models to model individual statistical learning
Hanna Ringer, Tatsuya Daikoku
Statistical learning is essential for individuals to discover structure in the sensory environment, especially during communication via speech or music. Individual differences in s…
AI Outperforms Humans in Personalized Image Aesthetics Assessment via LLM-Based Interviews and Semantic Feature Extraction
Yoshia Abe, Tatsuya Daikoku, Yasuo Kuniyoshi
Accurately predicting individual aesthetic evaluation for images is a fundamental challenge for AI. Various deep learning (DL)-based models have been proposed for this task, traini…
Interoceptive Divergence in Aesthetic Evaluation and Implications for Human-AI Alignment
Yoshia Abe, Tatsuya Daikoku, Yasuo Kuniyoshi
Artificial intelligence (AI), exemplified by large language models (LLMs), is rapidly approaching and in some cases surpassing human performance across a wide range of cognitive ta…
Emotional Responses to Auditory Hierarchical Structures is Shaped by Bodily Sensations and Listeners' Sensory Traits
Maiko Minatoya, Tatsuya Daikoku, Yasuo Kuniyoshi
Emotional responses to auditory stimuli are a common part of everyday life. However, for some individuals, these responses can be distressing enough to interfere with daily functio…
Assessing the Aesthetic Evaluation Capabilities of GPT-4 with Vision: Insights from Group and Individual Assessments
Yoshia Abe, Tatsuya Daikoku, Yasuo Kuniyoshi
Recently, it has been recognized that large language models demonstrate high performance on various intellectual tasks. However, few studies have investigated alignment with humans…
Shaping the Epochal Individuality and Generality: The Temporal Dynamics of Uncertainty and Prediction Error in Musical Improvisation
Tatsuya Daikoku
Musical improvisation, much like spontaneous speech, reveals intricate facets of the improviser's state of mind and emotional character. However, the specific musical components th…