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Sebastian Böck
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Improved musical onset detection with convolutional neural networks
J Schlüter, S Böck
2014 ieee international conference on acoustics, speech and signal …, 2014
3072014
Madmom: A new python audio and music signal processing library
S Böck, F Korzeniowski, J Schlüter, F Krebs, G Widmer
Proceedings of the 24th ACM international conference on Multimedia, 1174-1178, 2016
2822016
Universal onset detection with bidirectional long-short term memory neural networks
F Eyben, S Böck, B Schuller, A Graves
2162010
Polyphonic piano note transcription with recurrent neural networks
S Böck, M Schedl
2012 IEEE international conference on acoustics, speech and signal …, 2012
1892012
Evaluating the Online Capabilities of Onset Detection Methods.
S Böck, F Krebs, M Schedl
ISMIR, 49-54, 2012
1802012
Maximum filter vibrato suppression for onset detection
S Böck, G Widmer
Proc. of the 16th Int. Conf. on Digital Audio Effects (DAFx). Maynooth …, 2013
1692013
Joint Beat and Downbeat Tracking with Recurrent Neural Networks.
S Böck, F Krebs, G Widmer
ISMIR, 255-261, 2016
1572016
On the potential of simple framewise approaches to piano transcription
R Kelz, M Dorfer, F Korzeniowski, S Böck, A Arzt, G Widmer
arXiv preprint arXiv:1612.05153, 2016
1492016
Enhanced beat tracking with context-aware neural networks
S Böck, M Schedl
Proc. Int. Conf. Digital Audio Effects, 135-139, 2011
1382011
Rhythmic Pattern Modeling for Beat and Downbeat Tracking in Musical Audio.
F Krebs, S Böck, G Widmer
Ismir, 227-232, 2013
1132013
Accurate Tempo Estimation Based on Recurrent Neural Networks and Resonating Comb Filters.
S Böck, F Krebs, G Widmer
ISMIR, 625-631, 2015
1042015
A Multi-model Approach to Beat Tracking Considering Heterogeneous Music Styles.
S Böck, F Krebs, G Widmer
ISMIR, 603-608, 2014
982014
Online real-time onset detection with recurrent neural networks
S Böck, A Arzt, F Krebs, M Schedl
Proceedings of the 15th International Conference on Digital Audio Effects …, 2012
922012
An Efficient State-Space Model for Joint Tempo and Meter Tracking.
F Krebs, S Böck, G Widmer
ISMIR, 72-78, 2015
872015
Musical onset detection with convolutional neural networks
J Schlüter, S Böck
6th international workshop on machine learning and music (MML), Prague …, 2013
802013
Two data sets for tempo estimation and key detection in electronic dance music annotated from user corrections
P Knees, Á Faraldo Pérez, H Boyer, R Vogl, S Böck, F Hörschläger, ...
Proceedings of the 16th International Society for Music Information …, 2015
742015
Multi-Task Learning of Tempo and Beat: Learning One to Improve the Other.
S Böck, MEP Davies, P Knees
ISMIR, 486-493, 2019
662019
A low-latency, real-time-capable singing voice detection method with LSTM recurrent neural networks
B Lehner, G Widmer, S Bock
2015 23rd European signal processing conference (EUSIPCO), 21-25, 2015
582015
Temporal convolutional networks for musical audio beat tracking
EP MatthewDavies, S Böck
2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019
572019
Downbeat Tracking Using Beat Synchronous Features with Recurrent Neural Networks.
F Krebs, S Böck, M Dorfer, G Widmer
ISMIR, 129-135, 2016
572016
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