  Segregating an audio mixture containing multiple simultaneous bird sounds is
a challenging task. However, birdsong often contains rapid pitch modulations,
and these modulations carry information which may be of use in automatic
recognition. In this paper we demonstrate that an improved spectrogram
representation, based on the distribution derivative method, leads to improved
performance of a segregation algorithm which uses a Markov renewal process
model to track vocalisation patterns consisting of singing and silences.
