A Bayesian approach to convolutive nonnegative matrix factorization for blind speech dereverberation
- Ibarrola, Francisco Javier
- Di Persia, Leandro Ezequiel
- Spies, Ruben Daniel
DOIAbstract
When a signal is recorded in an enclosed room, it typically gets affected by reverberation. This degradation represents a problem when dealing with audio signals, particularly in the field of speech signal processing, such as automatic speech recognition. Although there are some approaches to deal with this issue that are quite satisfactory under certain conditions, constructing a method that works well in a general context still poses a significant challenge. In this article, we propose a Bayesian approach based on convolutive nonnegative matrix factorization that uses prior distributions in order to impose certain characteristics over the time-frequency components of the restored signal and the reverberant components. An algorithm for imp...
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