COMPARATIVE ANALYSIS OF LISTENER PERCEPTION AND EMOTIONAL RESPONSE TO AI-GENERATED AND HUMAN-COMPOSED MUSIC ACROSS MULTIPLE GENRES

Abstract

Recent developments in artificial intelligence have affected the creative industry, such as music composition, and present questions about the role of human creativity and listener perceptions. This research offers an empirical comparison of audience perceptions and emotional experiences of AI-composed versus human-composed music across various genres such as classical, rock and pop. Using a survey approach, a representative sample of listeners was asked to rate a set of audio clips, without knowledge of their authorship. Participants' assessments were captured through Likert-scale surveys that addressed aspects of listener perception including emotional response, creativity, authenticity and general listening quality. Data were explored handling descriptive and inferential statistical techniques to compare perceptions between types of music and genres. The results show that although AI-generated music is technically proficient and engaging, human-composed music consistently scores better in terms of emotional engagement and authenticity. Further analysis also revealed genre-specific differences with AI-generated music scoring better in structured genres rather than more free-form styles. The findings of this analyze will be instrumental in guiding musicians, technologists, and scholars on how to apply AI in their musical creations. Keywords: AI-Generated Music, Human-Composed Music, Listener Perception, Emotional Response, Music Genre Analysis