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Julien Osmalskyj - Publications ORBI
Osmalsky, J. (2017). A Combining Approach to Cover Song Identification. Unpublished doctoral thesis, Université de Liège, ​Liège, ​​Belgique.
This thesis is concerned with the problem of determining whether two songs are different versions of each other. This problem is known as the problem of cover song identification, which is a challenging task ...
Osmalsky, J., Van Droogenbroeck, M., & Embrechts, J.-J. (2016). Enhancing Cover Song Identification with Hierarchical Rank Aggregation. Proceedings of the 17th International for Music Information Retrieval Conference (pp. 136-142).
Peer reviewed
Abstract Cover song identification involves calculating pairwise similarities between a query audio track and a database of reference tracks. While most authors make exclusively use of chroma features, recent ...
Osmalsky, J., & Embrechts, J.-J. (2016). Effects of acoustic degradations on cover song identification systems. International Congress on Acoustics: ICA 2016.
Cover song identification systems deal with the problem of identifying different versions of an audio query in a reference database. Such systems involve the computation of pairwise similarity scores ... ...
Osmalsky, J., Embrechts, J.-J. (Other coll.), Foster, P. (Other coll.), & Dixon, S. (Other coll.). (2015). Combining Features for Cover Song Identification. 16th International Society for Music Information Retrieval Conference.
Peer reviewed
In this paper, we evaluate a set of methods for combining features for cover song identification. We first create multiple classifiers based on global tempo, duration, loudness, beats and chroma average ...
Osmalsky, J. (2015, February 24). Cover Songs Retrieval and Identification. Paper presented at Queen Mary University, Center For Digital Music Internal Seminar, London, UK.
Cover songs retrieval is a MIR task that has been widely studied in the recent years. The task, in its general sense, consists in retrieving covers for a given audio query. In this PhD, we focus on the ...
Osmalsky, J., Van Droogenbroeck, M., & Embrechts, J.-J. (2014). Performances of low-level audio classifiers for large-scale music similarity. International Conference on Systems, Signals and Image Processing (pp. 91-94).
Peer reviewed
This paper proposes a survey of the performances of binary classifiers based on low-level audio features, for music similarity in large-scale databases. Various low-level descriptors are used individually and ...
Osmalsky, J., Pierard, S., Van Droogenbroeck, M., & Embrechts, J.-J. (2013). Efficient database pruning for large-scale cover song recognition. International Conference on Acoustics, Speech, and Signal Processing (ICASSP). IEEE.
Peer reviewed
This paper focuses on cover song recognition over a large dataset, potentially containing millions of songs. At this time, the problem of cover song recognition is still challenging and only few methods have ...
Osmalsky, J., Embrechts, J.-J., Van Droogenbroeck, M., & Pierard, S. (2012). Neural networks for musical chords recognition. Journées d'informatique musicale (pp. 39-46).
Peer reviewed
In this paper, we consider the challenging problem of music recognition and present an effective machine learning based method using a feed-forward neural network for chord recognition. The method uses the ...