A mid-level representation for capturing dominant tempo and pulse information in music recordings

Abstract

Automated beat tracking and tempo estimation from music recordings become challenging tasks in the case of non-percussive music with soft note onsets and time-varying tempo. In this paper, we introduce a novel mid-level representation which captures predominant local pulse information. To this end, we first derive a tempogram by performing a local spectral analysis on a previously extracted, possibly very noisy onset representation. From this, we derive for each time position the predominant tempo as well as a sinusoidal kernel that best explains the local periodic nature of the onset representation. Then, our main idea is to accumulate the local kernels over time yielding a single function that reveals the predominant local pulse (PLP). We show that this function constitutes a robust mid-level representation from which one can derive musically meaningful tempo and beat information for non-percussive music even in the presence of significant tempo fluctuations. Furthermore, our representation allows for incorporating prior knowledge on the expected tempo range to exhibit information on different pulse levels.