Prior Structures for Time-Frequency Energy Distributions

We introduce a framework for probabilistic modelling of time-frequency energy distributions based on correlated Gamma and inverse Gamma random variables. One advantage of the approach is that the resulting class of models are conjugate which makes inference easier. Moreover, both positivity and additivity follow naturally in this framework. We illustrate how generic models (applicable to a broad class of signals) and more specialised models can be designed to model harmonicity, spectral continuity and/or changepoints. We show simulation results that illustrate the potential of the approach on a large spectrum of audio processing applications such as denoising, source separation and transcription.