Maarten Grachten
Maarten Grachten
Senior researcher, Department of Computational Perception, Johannes Kepler University, Linz
Verified email at - Homepage
TitleCited byYear
Melody retrieval using the implication/realization model
M Grachten, JL Arcos, R Lopez de Mantaras
YQX plays Chopin
G Widmer, S Flossmann, M Grachten
AI magazine 30 (3), 35, 2009
Melodic similarity: Looking for a good abstraction level
M Grachten, JL Arcos, RL De Mántaras
5th International Conference on Music Information Retrieval, 2004
The Magaloff project: An interim report
S Flossmann, W Goebl, M Grachten, B Niedermayer, G Widmer
Journal of New Music Research 39 (4), 363-377, 2010
Automatic alignment of music performances with structural differences
M Grachten, M Gasser, A Arzt, G Widmer
In Proceedings of 14th International Society for Music Information Retrieval …, 2013
Computational models of music perception and cognition I: The perceptual and cognitive processing chain
H Purwins, P Herrera, M Grachten, A Hazan, R Marxer, X Serra
Physics of Life Reviews 5 (3), 151-168, 2008
Expressive performance rendering: Introducing performance context
S Flossmann, M Grachten, G Widmer
Proceedings of the SMC, 155-160, 2009
Linear basis models for prediction and analysis of musical expression
M Grachten, G Widmer
Journal of New Music Research 41 (4), 311-322, 2012
Melodic characterization of monophonic recordings for expressive tempo transformations
E Gómez, M Grachten, X Amatriain, JL Arcos
Proceedings of Stockholm Music Acoustics Conference 2003, 2003
A case based approach to expressivity-aware tempo transformation
M Grachten, JL Arcos, RL De Mantaras
Machine Learning 65 (2-3), 411-437, 2006
Computational models of music perception and cognition II: Domain-specific music processing
H Purwins, M Grachten, P Herrera, A Hazan, R Marxer, X Serra
Physics of Life Reviews 5 (3), 169-182, 2008
The ISMIR Cloud: A Decade of ISMIR Conferences at Your Fingertips.
M Grachten, M Schedl, T Pohle, G Widmer
ISMIR, 63-68, 2009
Toward e-motion-based music retrieval a study of affective gesture recognition
D Amelynck, M Grachten, L Van Noorden, M Leman
IEEE Transactions on Affective Computing 3 (2), 250-259, 2012
Imposing Higher-Level Structure in Polyphonic Music Generation Using Convolutional Restricted Boltzmann Machines and Constraints
S Lattner, M Grachten, G Widmer
Journal of Creative Music Systems 2 (2), 2018
Phenicx: Performances as highly enriched and interactive concert experiences
E Gómez, M Grachten, A Hanjalic, J Janer, S Jorda, CF Julia, C Liem, ...
Proc. of SMC Sound and Music Computing Conference, 2013
Phase-plane representation and visualization of gestural structure in expressive timing
M Grachten, W Goebl, S Flossmann, G Widmer
Journal of New Music Research 38 (2), 183-195, 2009
An assessment of learned score features for modeling expressive dynamics in music
M Grachten, F Krebs
IEEE Transactions on Multimedia 16 (5), 1211-1218, 2014
Expressive performance rendering with probabilistic models
S Flossmann, M Grachten, G Widmer
Guide to Computing for Expressive Music Performance, 75-98, 2013
Who Is Who in the End? Recognizing Pianists by Their Final Ritardandi.
M Grachten, G Widmer
ISMIR, 51-56, 2009
Extracting performers’ behaviors to annotate cases in a cbr system for musical tempo transformations
JL Arcos, M Grachten, RL de Mántaras
International Conference on Case-Based Reasoning, 20-34, 2003
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