Harmonic Data: AI Music, EDM Transcription, & Minimalist Jazz

<p>This thesis presents research in the domains of music theory and music technology. The topics of the three chapters are as follows: (1) the technical and artistic limitations of artificial intelligence when generating music, (2) the transcription of electronic dance music (EDM) using a hybrid notation system, and (3) the effective convergence of jazz and minimalism in the music of Joe Hisaishi from Studio Ghibli. Each topic investigates a different aspect of harmony and the modern ways in which humans communicate in terms of harmony. The first chapter surveys the latest research projects in AI-generated music and proposes ideas for future applications of music generation using machine learning. The second chapter presents a hybrid notation system for the transcription of electronic dance music. The final chapter identifies progressive composition techniques embodied in the works of Japanese composer Joe Hisaishi, who borrows musical influence from around the world.</p>

Name thesis:degree_name

M.A.

Level thesis:degree_level

Masters Thesis

Year

2024

Author dc:creator

• Freed, Trevor

Contributors dc:contributor

• Mitchell Ohriner
• Kristin Taavola
• Sean Friar

• Artificial intelligence (AI)
• Electronic dance music (EDM)
• Hisaishi
• Minimalism
• Music
• Transcription
• Arts and Humanities
• Composition
• Music Theory
• Other Music

Statement dc:rights

• <p>Copyright is held by the author. User is responsible for all copyright compliance.</p>

Language dc:language

English (eng)

Repository record dc:identifier

https://digitalcommons.du.edu/etd/2368

OAI identifier oai:identifier

oai:digitalcommons.du.edu:etd-3359