The analysis of audio signals is central to the scientific understanding of human hearing abilities as well as in engineering applications such as sound localisation, hearing aids or music information retrieval. In recent years, there is an increasing interest for a Bayesian treatment and the application of graphical models which together permit increasingly refined analyses and representations of the acoustic signals. Such techniques are quite natural since acoustical time series can be conveniently modelled using hierarchical signal models by incorporating prior knowledge from physics or studies of human cognition and perception. The workshop will address advances in modelling and inference techniques for acoustics and how to integrate relevant prior information from sources such as neurobiology and form useful acoustic representations.