Hendrik Purwins
Hendrik Purwins
Center of Excellence for LLMs and GenAI, Accenture
E-mailová adresa ověřena na: - Domovská stránka
Deep learning for audio signal processing
H Purwins, B Li, T Virtanen, J Schlüter, SY Chang, T Sainath
IEEE Journal of Selected Topics in Signal Processing 13 (2), 206-219, 2019
Decoding auditory attention to instruments in polyphonic music using single-trial EEG classification
MS Treder, H Purwins, D Miklody, I Sturm, B Blankertz
Journal of neural engineering 11 (2), 026009, 2014
A new method for tracking modulations in tonal music in audio data format
H Purwins, B Blankertz, K Obermayer
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural …, 2000
Regression methods for virtual metrology of layer thickness in chemical vapor deposition
H Purwins, B Barak, A Nagi, R Engel, U Höckele, A Kyek, S Cherla, ...
IEEE/ASME Transactions on Mechatronics 19 (1), 1-8, 2013
Profiles of pitch classes circularity of relative pitch and key-experiments, models, computational music analysis, and perspectives
H Purwins
PhD Diss. Technische Universität Berlin, 2005
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
Sparse approximations for drum sound classification
S Scholler, H Purwins
IEEE Journal of Selected Topics in Signal Processing 5 (5), 933-940, 2011
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
Toroidal models in tonal theory and pitch-class analysis.
H Purwins, B Blankertz, K Obermayer
Computing in musicology 15, 2007
Convolutional neural networks with batch normalization for classifying hi-hat, snare, and bass percussion sound samples
N Gajhede, O Beck, H Purwins
Proceedings of the Audio Mostly 2016, 111-115, 2016
Unsupervised incremental online learning and prediction of musical audio signals
R Marxer, H Purwins
IEEE/ACM Transactions on Audio, Speech, and Language Processing 24 (5), 863-874, 2016
Correspondence analysis for visualizing interplay of pitch class, key, and composer
H Purwins, T Graepel, B Blankertz, K Obermayer
Perspectives in mathematical and computational music theory, Osnabrück …, 2004
Regression methods for prediction of PECVD Silicon Nitride layer thickness
H Purwins, A Nagi, B Barak, U Höckele, A Kyek, B Lenz, G Pfeifer, ...
2011 IEEE International Conference on Automation Science and Engineering …, 2011
Closing the loop of sound evaluation and design
P Susini, N Misdariis, G Lemaitre, O Houix, D Rocchesso, P Polotti, ...
Perceptual Quality of Systems 2 (4), 2006
Computing auditory perception
H Purwins, B Blankertz, K Obermayer
Organised Sound 5 (3), 159-171, 2000
Model cortical responses for the detection of perceptual onsets and beat tracking in singing
M Coath, SL Denham, LM Smith, H Honing, A Hazan, P Holonowicz, ...
Connection Science 21 (2-3), 193-205, 2009
What/when causal expectation modelling applied to audio signals
A Hazan, R Marxer, P Brossier, H Purwins, P Herrera, X Serra
Connection Science 21 (2-3), 119-143, 2009
Constant Q profiles for tracking modulations in audio data
P Purwins, B Blankertz, K Obermayer
International Computer Music Conference, 2001
Dynamical hierarchical self-organization of harmonic, motivic, and pitch categories
R Marxer, P Holonowicz, H Purwins, A Hazan
Music, Brain and Cognition. Part 2, 2007
A graphical representation and dissimilarity measure for basic everyday sound events
K Adiloglu, A Annies, E Wahlen, H Purwins, K Obermayer
IEEE Transactions on Audio, Speech, and Language Processing 20 (5), 1542-1552, 2012
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Články 1–20