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Heraeus Dissertation Prize

Faculty Prize 2025 awarded to two outstanding doctoral theses   more ...
© MARTIN LIEBETRUTH

Forum Wissen Award 2025 for Astrid Eichhorn

Recognition for outstanding science communication   more ...
MATTHIAS BARTELMANN

A Prize for Clarity, Curiosity, and the Art of Explanation

The DPG honors Matthias Bartelmann for outstanding achievements in teaching and science communication   more ...
PEER FISCHER

Light-Driven Nanodevices

Peer Fischer awarded ERC Synergy Grant for pioneering DNA-based nanosystems   more ...
4MOST Consortium

4MOST captures “First Light” at Paranal Observatory

New world-class survey facility with Heidelberg expertise begins its scientific operations   more ...
ELISA SCHÖSSER

Ernst Patzer Prize awarded to Elisa Schösser

ZAH doctoral researcher honored for discovery of extremely iron-poor massive stars   more ...
Dr. Victor Ksoll (© Kerstin Schmid / Foto Sauer)

Carl Zeiss Foundation funds new research project at ZAH

€1.8 million for new research group at the Institute for Theoretical Astrophysics   more ...
MIRACULUM BY HELENA KLUSSMANN

Fresh Perspectives for the Department

Johanna Schwarz shares first impressions and her view on future priorities.   more ...
JULIAN SCHMITT

Quantum sites in the Quantum Year 2025

The “100 quantum sites” page for the quantum year is online   more ...

Physics colloquium

Friday, 19. December 2025 5:00 pm  Artificial Intelligence and Music: On the Role of AI in Studying a Human Art Form

Prof. Dr. Gerhard Widmer , Institut für Computational Perception, Universität Linz

The field of AI & Music has come a long way, from early attempts at algorithmic composition to a wide variety of intelligent sound and music technologies that are shaping today's digital music world. As in many other application domains, many of the recent successes are based on exploiting and adapting the latest advances in statistical machine learning, transferring them from fields like computer vision and language processing.
But music is much more than just an acoustic signal with hidden patterns, or a sequence of events with statistical properties. Music is a deeply human art, a unique means of human self-expression and emotional communication, and we still lack a full understanding of how music "works", as a communication language between composers, performers, and listeners.
I will try to demonstrate that AI and machine learning may have something to contribute here, by providing means of studying some of these questions via computational modeling. We will focus on the complex phenomenon of expressivity in music performance (of classical music): how skilled performers make music "come alive" and communicate subtle aspects like moods, ideas, emotions through their playing. I will take the audience through a recent big research project that aimed at studying certain aspects of this with machine learning. We will see what it takes to model and explore such an elusive concept in a data-driven way, talk about the difficulty of obtaining reliable data, but also about the difficulty of evaluating the results, and how we may nevertheless obtain some interesting and possibly useful results. We will see (and hear) computer models of expressive playing and human-machine piano co-performance, and we will even learn about an expressive performance system that allegedly passed a musical "Turing Test". However, we will also find (or I will contend) that the very idea of a "Turing Test" in this context (and perhaps generally in the arts) may be fundamentally problematic. At a more general level, I will argue that we should carefully consider the proper role of AI in music, if we take music seriously as an expressive (human) art form.


 

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