Christoph Finkensiep
Assistant Professor in Generative AI in the Arts
Christoph’s research focuses on understanding musical structure and musical systems through computational models. In his PhD project, he investigated the interaction of harmony, voice leading, and ornamentation in free polyphonic music. His current work involves hybrid probabilistic and neural models of music structure, and corpus studies using Bayesian models. Further scientific interests include music cognition, aesthetics, cultural evolution, as well as philosophy of mind and philosophy of science.
Latest publications
Cecchetti, G., Finkensiep, C., Guan, X., Herff, S. A., Fiveash, A., Pelofi, C., & Drury, J. E. (2023). Music Cognition between Theory and Experiment. 38–39. https://cognitivesciencesociety.org/cogsci-2023/
Christoph Finkensiep, Matthieu Haeberle, Friedrich Eisenbrand, Markus Neuwirth, & Martin Rohrmeier. (2023). Repetition-Structure Inference With Formal Prototypes. ISMIR.
DOI
10.5281/ZENODO.10265304
Neuwirth, M., Finkensiep, C., & Rohrmeier, M. (2023). Musical Schemata: Modelling Challenges and Pattern Finding (BachBeatles). In Digital Humanities Research (pp. 147–164). Bielefeld University Press / transcript Verlag.
DOI
10.14361/9783839469132-016
Cecchetti, G., Herff, S. A., Finkensiep, C., Harasim, D., & Rohrmeier, M. A. (2022). Hearing functional harmony in jazz: A perceptual study of music-theoretical accounts of extended tonality. Musicae Scientiae, 27(3), 672–697.
DOI
10.1177/10298649221122245
Finkensiep, C., & Rohrmeier, M. A. (2021). Modeling and Inferring Proto-Voice Structure in Free Polyphony. Zenodo.
DOI
10.5281/ZENODO.5624430
Harasim, D., Finkensiep, C., Bigo, L., Giraud, M., Levé, F., Shanahan, D., Sears, D. R. W., & Rohrmeier, M. (2021). Music Cognition: The Complexity of Musical Structure. 35–36.
Herff, S. A., Harasim, D., Cecchetti, G., Finkensiep, C., & Rohrmeier, M. A. (2021). Hierarchical syntactic structure predicts listeners’ sequence completion in music. Proceedings of the Annual Meeting of the Cognitive Science Society, 43, 903–909.
Finkensiep, C., Déguernel, K., Neuwirth, M., & Rohrmeier, M. (2020). Voice-leading schema recognition using rhythm and pitch features.
DOI
10.5281/ZENODO.4245482
Harasim, D., Finkensiep, C., Ericson, P., O’Donnell, T. J., & Rohrmeier, M. (2020). The jazz Harmony Treebank.
DOI
10.5281/ZENODO.4245406
Cecchetti, G., Herff, S. A., Finkensiep, C., & Rohrmeier, M. A. (2020). The experience of musical structure as computation : what can we learn? [JD]. Rivista Di Analisi e Teoria Musicale : XXVI, 2, 2020, 2.
DOI
10.53152/1032
Students
Yikun Gu
Master Artificial Intelligence, UvA•2024
Andrei Blahovici
Master Artificial Intelligence, UvA•2024
Music Cognition Group
The Music Cognition Group is part of the Department of Musicology, the Institute for Logic, Language and Computation, and Amsterdam Brain and Cognition of the University of Amsterdam.
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