General Concept with the Joint Diagonalization of the Speech and Noise Correlation Matrices
Abstract
In the previous chapter, we showed how the eigenvalue decomposition of the speech correlation matrix can be exploited in the derivation of different types of optimal filtering matrices for the general problem of speech enhancement. This chapter attempts to show the same results but with the joint diagonalization of the speech and noise correlation matrices. We will see that there are some subtle differences between these two approaches with many more possibilities with joint diagonalization, suggesting that this tool is very natural to use in this problem.
Keywords
Joint diagonalization; Performance measures; Optimal filtering matrices; ...
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