Florian Krebs
Florian Krebs
Joanneum Research Graz
Keine bestätigte E-Mail-Adresse
Zitiert von
Zitiert von
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
Evaluating the Online Capabilities of Onset Detection Methods.
S Böck, F Krebs, M Schedl
ISMIR, 49-54, 2012
Joint Beat and Downbeat Tracking with Recurrent Neural Networks.
S Böck, F Krebs, G Widmer
ISMIR, 255-261, 2016
Rhythmic Pattern Modeling for Beat and Downbeat Tracking in Musical Audio.
F Krebs, S Böck, G Widmer
Ismir, 227-232, 2013
Accurate Tempo Estimation Based on Recurrent Neural Networks and Resonating Comb Filters.
S Böck, F Krebs, G Widmer
ISMIR, 625-631, 2015
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
A Multi-model Approach to Beat Tracking Considering Heterogeneous Music Styles.
S Böck, F Krebs, G Widmer
ISMIR, 603-608, 2014
An Efficient State-Space Model for Joint Tempo and Meter Tracking.
F Krebs, S Böck, G Widmer
ISMIR, 72-78, 2015
Downbeat Tracking Using Beat Synchronous Features with Recurrent Neural Networks.
F Krebs, S Böck, M Dorfer, G Widmer
ISMIR, 129-135, 2016
Social emotion mining techniques for Facebook posts reaction prediction
F Krebs, B Lubascher, T Moers, P Schaap, G Spanakis
arXiv preprint arXiv:1712.03249, 2017
Tracking the “odd”: Meter inference in a culturally diverse music corpus
A Holzapfel, F Krebs, A Srinivasamurthy
ISMIR-International Conference on Music Information Retrieval, 425-430, 2014
Bridging the audio-symbolic gap: The discovery of repeated note content directly from polyphonic music audio
T Collins, S Böck, F Krebs, G Widmer
Audio Engineering Society Conference: 53rd International Conference …, 2014
A three-dimensional study of the glottal jet
F Krebs, F Silva, D Sciamarella, G Artana
Experiments in fluids 52 (5), 1133-1147, 2012
Inferring metrical structure in music using particle filters
F Krebs, A Holzapfel, AT Cemgil, G Widmer
IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (5), 817-827, 2015
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
Tracking rests and tempo changes: Improved score following with particle filters
F Korzeniowski, F Krebs, A Arzt, G Widmer
ICMC, 2013
Unsupervised learning and refinement of rhythmic patterns for beat and downbeat tracking
F Krebs, F Korzeniowski, M Grachten, G Widmer
2014 22nd European Signal Processing Conference (EUSIPCO), 611-615, 2014
Combining score and filter based models to predict tempo fluctuations in expressive music performances
F Krebs, M Grachten
Proceedings of the Ninth Sound and Music Computing Conference (SMC), 358-363, 2012
SEMTec: Social emotion mining techniques for analysis and prediction of Facebook post reactions
T Moers, F Krebs, G Spanakis
International Conference on Agents and Artificial Intelligence, 361-382, 2018
Mirex submissions for chord recognition and key estimation 2017
F Korzeniowski, S Böck, F Krebs, G Widmer
MIREX evaluation results, 2017
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