Artificial Intelligence in Music, Winter Term 2025/2026

Overview

The goal of this course is to provide an introduction into the research field Artificial Intelligence (AI) in music using traditional and modern algorithms, including music information retrieval (MIR) and machine learning (ML) approaches: basics of digital music processing, extraction of various features from audio, score, and other music related data, classification scenarios, music generation and algorithm evaluation, etc.

The course is organised into four segments:

• Foundations: backgrounds of music data processing and analysis of different modalities (audio, score, text, images, social data, etc.)
• Mid-Level Features: application of supervised classification to predict semantically meaningful descriptors of music pieces
• High-Level Categories: methods to organise music collections (e.g., based on genres or emotions), recommendation systems, user friendly evaluation
• Music Generation: from rule-based systems to text-to-music models

Another key component of this course is the critical evaluation of AI methods for music related applications from different perspectives including classification quality, interpretability, robustness, and resources.

The lecture will take place at the Chair for Artificial Intelligence Methodology (Theaterstr. 35-39, room 325), on Thursdays during the winter term, 10:30-12:00, following with the exercise, 12:15-13:30.

The working language is English.

Registration

Registration to the lecture is handled via the RWTH Online and the number of places is limited to 20.

Organisers

Prof. Dr. Holger H. Hoos Chair Holder, Alexander von Humboldt Professor

E-mail: hh[at]aim[dot]rwth-aachen[dot]de
Phone: +49 241 80 21451

Dr. Igor Vatolkin Assistant Professor (Akademischer Rat)

E-mail: vatolkin[at]aim[dot]rwth-aachen[dot]de

M.Sc. Justin Dettmer PhD Student

E-mail: dettmer[at]aim[dot]rwth-aachen[dot]de