Go to JKU Homepage
Institute of Computational Perception
What's that?

Institutes, schools, other departments, and programs create their own web content and menus.

To help you better navigate the site, see here where you are at the moment.

Whither Music?

Exploring Musical Possibilities via Machine Simulation

Scientific Publications

Transparent Performance Models

Cancino Chacon, C., Peter, S. and Widmer, G. (2022).
Can We Achieve Togetherness with an Artificial Partner? Insights and Challenges from Developing an Automatic Accompaniment System.
In Musical Togetherness Symposium (MTS-22), Vienna, Austria. (to appear)

Explainable and Robust Perception Models

Foscarin, F., Hoedt, K., Praher, V., Flexer, A. and Widmer, G. (2022).
Concept-Based Techniques for Musicologist-Friendly Explanations of Deep Music Classifiers.
In Proceedings of the 23rd International Society for Music Information Retrieval Conference (ISMIR 2022), Bengaluru, India. (to appear)

Karystinaios, E. and Widmer, G. (2022).
Cadence Detection in Symbolic Classical Music using Graph Neural Networks.
In Proceedings of the 23rd International Society for Music Information Retrieval Conference (ISMIR 2022), Bengaluru, India. (to appear)

Prinz, K., Flexer, A. and Widmer, G. (2022). [Code, opens an external URL in a new window]
Defending a Music Recommender Against Hubness-Based Adversarial Attacks, opens an external URL in a new window.
In Proceedings of the 2022 Sound and Music Computing (SMC 2022), Saint-Etienne, France.

Musical Data, Representations, Fundamental Technologies

Cancino-Chacón, C., Peter, S., Karystinaios, E., Foscarin, F., Grachten, M. and Widmer, G. (2022). [ Code, opens an external URL in a new window ]
Partitura: A Python Package for Symbolic Music Processing, opens an external URL in a new window.
In Proceedings of the Music Encoding Conference (MEC 2022), Halifax, Canada.

Foscarin, F., Karystinaios, E., Peter, S., Cancino-Chacón, C., Grachten, M. and Widmer, G. (2022). [Doc, opens an external URL in a new window | Data, opens an external URL in a new window ]
The match File Format: Encoding Alignments between Scores and Performances, opens an external URL in a new window.
In Proceedings of the Music Encoding Conference (MEC 2022), Halifax, Canada.

Henkel, F. (2022). [Code, opens an external URL in a new window]
Multi-modal Deep Learning for On-line Music Following in Score Sheet Images, opens an external URL in a new window.
PhD. Thesis, Inst. of Computational Perception, Johannes Kepler University Linz, Austria.

Acknowledgment

This project receives funding from the European Research Council (ERC), opens an external URL in a new window under the European Union's Horizon 2020 research and innovation programme under grant agreement No 101019375 (Whither Music?).