TY - CONF T1 - Improving Music Recommendations with a Weighted Factorization of the Tagging Activity T2 - Proceedings of the 16th International Society for Music Information Retrieval Conference (ISMIR) Y1 - 2015 A1 - Andreu Vall A1 - Marcin Skowron A1 - Peter Knees A1 - Markus Schedl JF - Proceedings of the 16th International Society for Music Information Retrieval Conference (ISMIR) CY - Malaga, Spain ER - TY - CONF T1 - Music Retrieval and Recommendation – A Tutorial Overview T2 - Proceedings of the 38th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) Y1 - 2015 A1 - Peter Knees A1 - Markus Schedl JF - Proceedings of the 38th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) CY - Santiago, Chile ER - TY - JOUR T1 - An Assessment of Learned Score Features for Modeling Expressive Dynamics in Music JF - {IEEE} Transactions on Multimedia Y1 - 2014 A1 - M. Grachten A1 - F. Krebs VL - 16 UR - http://dx.doi.org/10.1109/TMM.2014.2311013 ER - TY - CONF T1 - Bridging the Audio-Symbolic Gap: The Discovery of Repeated Note Content Directly from Polyphonic Music Audio T2 - 53rd AES Conference on Semantic Audio Y1 - 2014 A1 - Collins, Tom A1 - Sebastian Böck A1 - Krebs, Florian A1 - Widmer, Gerhard JF - 53rd AES Conference on Semantic Audio CY - London, UK ER - TY - JOUR T1 - The impact of hesitation, a social signal, on a user’s quality of experience in multimedia content retrieval JF - Springer Multimedia Tools and Applications Y1 - 2014 A1 - Vodlan, Tomaż A1 - Tkalčič, Marko A1 - Košir, Andrej KW - computer interaction KW - hesitation KW - human KW - social signals KW - video-on-demand UR - http://link.springer.com/10.1007/s11042-014-1933-2 ER - TY - CONF T1 - SoMeRA 2014: Social Media Retrieval and Analysis Workshop T2 - Proceedings of the 37th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) Y1 - 2014 A1 - Markus Schedl A1 - Peter Knees A1 - Jialie Shen JF - Proceedings of the 37th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) CY - Gold Coast, Australia ER - TY - CONF T1 - Using Social Media Mining for Estimating Theory of Planned Behaviour Parameters T2 - Proceedings of the 2nd Workshop on Emotions and Personality in Personalized Services (EMPIRE 2014) Y1 - 2014 A1 - Marko Tkalčič A1 - Bruce Ferwerda A1 - Markus Schedl A1 - Cynthia C. S. Liem A1 - Mark S. Melenhorst A1 - Ante Odić A1 - Andrej Košir JF - Proceedings of the 2nd Workshop on Emotions and Personality in Personalized Services (EMPIRE 2014) CY - Aalborg, Denmark ER - TY - CONF T1 - How to Improve the Statistical Power of the 10-fold Cross Validation Scheme in Recommender Systems T2 - Proceedings of the International Workshop on Reproducibility and Replication in Recommender Systems Evaluation Y1 - 2013 A1 - Košir, Andrej A1 - Odić, Ante A1 - Tkalčič, Marko KW - evaluation KW - experimental design KW - folding KW - paired testing KW - recommender systems JF - Proceedings of the International Workshop on Reproducibility and Replication in Recommender Systems Evaluation PB - ACM CY - New York, NY, USA SN - 978-1-4503-2465-6 UR - http://doi.acm.org/10.1145/2532508.2532510 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 - CONF T1 - The Million Musical Tweets Dataset: What Can We Learn From Microblogs T2 - Proceedings of the 14th International Society for Music Information Retrieval Conference (ISMIR 2013) Y1 - 2013 A1 - David Hauger A1 - Markus Schedl A1 - Andrej Košir A1 - Marko Tkalčič JF - Proceedings of the 14th International Society for Music Information Retrieval Conference (ISMIR 2013) CY - Curitiba, Brazil ER - TY - CONF T1 - Personality and Social Context: Impact on Emotion Induction from Movies T2 - EMPIRE 2013: Emotions and Personality in Personalized Services Y1 - 2013 A1 - Ante Odić A1 - Marko Tkalčič A1 - Jurij F. Tasič A1 - Andrej Košir AB -
In this paper we describe our preliminary work on understanding the impact of personality on the emotion induction in di erent social circumstances during the consumption of movies, for the purposeof the context-aware recommender system for movies. The purpose ofthis study is to answer two research questions: is there a di erence in emotion induction when users are alone as opposed to when they are with company during watching the movie, and do di erent personality pro les in uence the emotion induction when users are alone as opposed to when they are with company during watching the movie? We have used the (LDOS-CoMoDa) dataset which contains ratings and associated contextual information for the consumed movies, as well as Big Five personality pro les of the users. The results showed that there is an in uence of social context on emotion induction, and that personality factors have to be taken into consideration since for the di erent groups of users, based on the personality factors, the emotion induction was in uenced di erently
JF - EMPIRE 2013: Emotions and Personality in Personalized Services PB - http://ceur-ws.org/Vol-997/#empire2013 CY - Rome, Italy UR - http://ceur-ws.org/Vol-997/empire2013_paper_5.pdf ER - TY - CONF T1 - Refined Spectral Template Models for Score Following T2 - Proceedings of the Sound and Music Computing Conference (SMC) Y1 - 2013 A1 - Korzeniowski, Filip A1 - Widmer, Gerhard AB - Score followers often use spectral templates for notes and chords to estimate the similarity between positions in the score and the incoming audio stream. Here, we propose two methods on different modelling levels to improve the quality of these templates, and subsequently the quality of the alignment. The first method focuses on creating more informed tem- plates for individual notes. This is achieved by estimating the template based on synthesised sounds rather than generic Gaussian mixtures, as used in current state-of-the-art systems. The second method introduces an advanced approach to aggregate individual note templates into spectral templates representing a specific score position. In contrast to score chordification, the common procedure used by score fol- lowers to deal with polyphonic scores, we use weighting functions to weight notes, observing their temporal relationships. We evaluate both methods against a dataset of classical piano music to show their positive impact on the alignment quality. JF - Proceedings of the Sound and Music Computing Conference (SMC) CY - Stockholm, Sweden ER - TY - Generic T1 - Rhytmic Pattern Modeling for Beat and Downbeat Tracking in Musical Audio T2 - Proceedings of the 14th International Society for Music Information Retrieval Conference (ISMIR 2013) Y1 - 2013 A1 - Krebs, Florian A1 - Sebastian Böck A1 - Widmer, Gerhard AB -

Rhythmic patterns are an important structural element in music. This paper investigates the use of rhythmic pattern modeling to infer metrical structure in musical audio recordings. We present a Hidden Markov Model (HMM) based system that simultaneously extracts beats, downbeats, tempo, meter, and rhythmic patterns. Our model builds upon the basic structure proposed by Whiteley et. al, which we further modified by introducing a new observation model: rhythmic patterns are learned directly from data, which makes the model adaptable to the rhythmical structure of any kind of music. For learning rhythmic patterns and evaluating beat and downbeat tracking, 697 ballroom dance pieces were annotated with beat and measure information. The results showed that explicitly modeling rhythmic patterns of dance styles drastically reduces octave errors (detection of half or double tempo) and substantially improves downbeat tracking.

JF - Proceedings of the 14th International Society for Music Information Retrieval Conference (ISMIR 2013) ER - TY - CONF T1 - Tracking Rests and Tempo Changes: Improved Score Following with Particle Filters T2 - Proceedings of the International Computer Music Conference (ICMC) Y1 - 2013 A1 - Korzeniowski, Filip A1 - Krebs, Florian A1 - Andreas Arzt A1 - Widmer, Gerhard AB -

In this paper we present a score following system based on a Dynamic Bayesian Network, using particle filtering as inference method. The proposed model sets itself apart from existing approaches by including two new extensions: A multi-level tempo model to improve alignment quality of performances with challenging tempo changes, and an extension to reflect different expressive characteristics of notated rests. Both extensions are evaluated against a dataset of classical piano music. As the results show, the extensions improve both the accuracy and the robustness of the algorithm.

JF - Proceedings of the International Computer Music Conference (ICMC) CY - Perth, Australia ER -