TY  - CONF
T1  - Listener-aware Music Recommendation from Sensor and Social Media Data
T2  - Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2015)
Y1  - 2015
A1  - Markus Schedl
JF  - Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2015)
CY  - Porto, Portugal
ER  - 

TY  - CONF
T1  - Listener-aware Music Search and Recommendation
T2  - Proceedings of the 6th International Workshop on Mining Ubiquitous and Social Environments (MUSE 2015)
Y1  - 2015
A1  - Markus Schedl
JF  - Proceedings of the 6th International Workshop on Mining Ubiquitous and Social Environments (MUSE 2015)
CY  - Porto, Portugal
ER  - 

TY  - CONF
T1  - Location-Aware Music Artist Recommendation
T2  - Proceedings of the 20th International Conference on MultiMedia Modeling (MMM 2014)
Y1  - 2014
A1  - Markus Schedl
A1  - Dominik Schnitzer
JF  - Proceedings of the 20th International Conference on MultiMedia Modeling (MMM 2014)
CY  - Dublin, Ireland
ER  - 

TY  - CONF
T1  - Local Group Delay based Vibrato and Tremolo Suppression for Onset Detection
T2  - Proceedings of the 14th International Society for Music Information Retrieval Conference (ISMIR 2013)
Y1  - 2013
A1  - Sebastian Böck
A1  - Widmer, Gerhard
KW  - local group delay
KW  - onset detection
KW  - tremolo suppression
KW  - vibrato suppression
AB  - <p>We present SuperFlux - a new onset detection algorithm with vibrato suppression. It is an enhanced version of the universal spectral flux onset detection algorithm, and reduces the number of false positive detections considerably by tracking spectral trajectories with a maximum filter. Especially for music with heavy use of vibrato (e.g., sung operas or string performances), the number of false positive detections can be reduced by up to 60% without missing any additional events. Algorithm performance was evaluated and compared to state-of-the-art methods on the basis of three different datasets comprising mixed audio material (25,927 onsets), violin recordings (7,677 onsets) and operatic solo voice recordings (1,448 onsets). Due to its causal nature, the algorithm is applicable in both offline and online real-time scenarios.</p>
JF  - Proceedings of the 14th International Society for Music Information Retrieval Conference (ISMIR 2013)
CY  - Curitiba, Brazil
ER  - 

TY  - CONF
T1  - Location-aware Music Recommendation Using Auto-Tagging and Hybrid Matching
T2  - Proceedings of the 7th ACM Conference on Recommender Systems (RecSys 2013)
Y1  - 2013
A1  - Marius Kaminskas
A1  - Francesco Ricci
A1  - Markus Schedl
JF  - Proceedings of the 7th ACM Conference on Recommender Systems (RecSys 2013)
CY  - Hong Kong, China
ER  - 

TY  - Generic
T1  - Looking Beyond Sound: Unsupervised Analysis of Musician Videos
T2  - 14th International Workshop on Image and Audio Analysis for Multimedia Interactive services (WIA2MIS)
Y1  - 2013
A1  - Cynthia C. S. Liem
A1  - Alessio Bazzica
A1  - Alan Hanjalic
AB  - <div>  	In this work, we focus on visual information conveyed by performing musicians. While musicians are playing, their movement relates to their musical performance. As such, analysis of this information can support structural characterization and timeline indexing of a recorded performance, especially in cases when such analyses are not trivially computed from the musical audio. We propose an unsupervised visual analysis method, in which visual novelty is inferred from motion orientation histograms of regions of interest. Considering our method in a case study on audiovisually recorded jam sessions, we show that our analysis of the visual channel yields promising and meaningful performance-related information, including information complementary to the audio channel.</div>
JF  - 14th International Workshop on Image and Audio Analysis for Multimedia Interactive services (WIA2MIS)
PB  - IEEE
CY  - Paris, France
ER  - 

TY  - CONF
T1  - Low-latency Bass Separation using Harmonic-Percussion Decomposition
T2  - International Conference on Digital Audio Effects Conference (DAFx-13)
Y1  - 2013
A1  - Marxer, R.
A1  - Janer, J.
AB  - <p>Many recent approaches to musical source separation rely on model-based inference methods that take into account the signal’s harmonic structure. To address the particular case of low-latency bass separation, we propose a method that combines harmonic decomposition using a Tikhonov regularization-based algorithm, with the peak contrast analysis of the pitch likelihood function. Our experiment compares the separation performance of this method to a naive low-pass filter, a state-of-the-art NMF-based method and a near-optimal binary mask. The proposed low-latency method achieves results similar to the NMF-based high-latency approach at a lower computational cost. Therefore the method is valid for real-time implementations.</p>
JF  - International Conference on Digital Audio Effects Conference (DAFx-13)
CY  - Maynooth, Ireland
UR  - http://dafx13.nuim.ie/papers/11.dafx2013_submission_13.pdf
ER  -