University of Cambridge > > Signal Processing and Communications Lab Seminars > Probabilistic modelling of time-frequency representations with application to music signals

Probabilistic modelling of time-frequency representations with application to music signals

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Prof. Ramji Venkataramanan.

Nonnegative Matrix Factorization (NMF) is a powerful tool for decomposing mixtures of non-stationary signals in the Time-Frequency (TF) domain. In the literature, a variety of probabilistic models involving latent variables have been designed for introducing some a priori knowledge (like harmonicity and smoothness) into NMF . However, phases are generally ignored in such models, which results in a limited spectral resolution (sinusoids in the same frequency band cannot be properly separated). Moreover, most of these models assume that all TF coefficients are independent, which is not the case of sinusoidal signals for instance. In this talk, I will present a unified probabilistic model called HR-NMF, which achieves a high spectral resolution by taking both phases and local correlations in each frequency band into account. The potential of this new approach will be illustrated in the context of audio source separation and audio inpainting.

This talk is part of the Signal Processing and Communications Lab Seminars series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.


© 2006-2023, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity