Improving Beat Tracking in the presence of highly predominant vocals using source separation techniques: Preliminary study Jos´ e R. Zapata and Emilia G´ omez Music Technology Group Universitat Pompeu Fabra {joser.zapata,emilia.gomez}@upf.edu Abstract. The automatic beat tracking from audio is still an open re- search task in the Music Information Retrieval (MIR) community. The goal of this paper is to show and discuss a work-in-progress of how audio source separation can be used for improving beat tracking estimations in difficult cases of music audio signal with highly predominant vocals. The audio source separation using FASST (Flexible Audio Source Separa- tion Toolbox) had an average improvement of beat tracking of {14,15%, 17,74%} in the F-measure and {14,21%, 25,70%} in the Amlt of Klapuri and Degara systems respectably in a dataset of 20 songs excerpt. Keywords: Beat tracking, Source separation, Predominant voice 1 Introduction The task of Beat tracking is related to the detection of the main pulse beat, defined as “one of a series of regularly recurring, precisely equivalent stimuli” [1]. For Western music, a hierarchical metrical structure is found in different time scales, and the most common ones are: the tatum period, defined as “a regular time division that mostly coincides with all note onsets”; and the tactus period (the perceptually most prominent period), defined as the rate at which most people would regularly tap their feet, hands or finger in time following the music. Beat is a relevant audio descriptor of a piece of music, which represents the speed of the piece under study. For that reason, much research within the Music Information Retrieval (MIR) community has been devoted to finding ways to automate its extraction and many algorithms have been proposed. Beat track- ing algorithms have been used in different application contexts, such as music retrieval, cover detection, playlist generation, and beat synchronization for au- dio mixing, structural analysis and score alignment. Many approaches for beat tracking have been proposed, and some efforts have been devoted to their quan- titative comparisons to find other ways to emphasize and detect the rhythm accents in music, but it’s not still clear in which kind of music or interpretations the beat trackers have problems to detect the beats.