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Express Paper Open Access

Subjective Evaluation of Emotions in Music Generated by Artificial Intelligence

Authors: Stairs, Holt; Bulla, Wesley; Chon, Song Hui

Express Paper · Paper 294 · September 2024

Abstract

Artificial Intelligence (AI) models offer consumers a resource that will generate music in a variety of genres and with a range of emotions with only a text prompt. However, emotion is a complex human phenomenon which becomes even more complex when attempted to convey through music. There is limited research assessing AIs capability to generate music with emotion. Utilizing specified target emotions this study examined the validity of these emotions as expressed in AI-generated musical samples. Seven audio engineering graduate students listened to 144 AI-generated musical examples with 16 emotions in three genres and reported their impression of the most appropriate emotion for each stimulus. Using Cohens kappa minimal agreement was found between subjects and AI. Results suggest that generating music with a specific emotion is still challenging for AI. Additionally, the AI model here appeared to operate with a predetermined group of musical samples linked to similar emotions. Discussion includes how this rapidly changing technology might be better studied in the future.

Details

AES Convention
157
Paper number
294
Publication date
September 27, 2024
Affiliation
M.S. Audio Engineering, Mike Curb College of Entertainment and Music Business, Belmont University; M.S. Audio Engineering, Mike Curb College of Entertainment and Music Business, Belmont University; M.S. Audio Engineering, Mike Curb College of Entertainment and Music Business, Belmont University (See document for exact affiliation information.)
Type
Express Paper