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.