A semi-blind approach to the separation of real world speech mixtures

The possibility of introducing a-priori information into multichannel blind deconvolution algorithms is investigated. The maximum likelihood (ML) approach allows one to introduce an important feature of the voice, namely the pitch, naturally into the ´blind´ model, removing the nonlinearity and showing the advantages of productive contaminations by such related research fields as computer-aided sound analysis (CASA) and Bayesian theory