Robust detection of jittered multiply repeating audio events using iterated time-warped ACF

This paper proposes a novel approach for robustly detecting multiply repeating audio events in monitoring recordings. We consider the practically important case that the sequence of inter onset intervals between subsequent events is not constant but differs by some jitter. In such cases classical approaches based on autocorrelation (ACF) are of limited use. To overcome this problem we propose to use ACF together with a variant of dynamic time warping. Combining both techniques in an iterative algorithm, we obtain a method for significantly improved detection of jittered multiply repeating events. In this paper we describe the new iterated time-warped ACF algorithm and evaluate its performance on the bioacoustic application of detecting repeating bird calls in monitoring recordings