Speech Denoising Using Variant of Minimum Controlled Recursive Average Algorithm and PCA
نویسندگان
چکیده
Speech denoising is very important in many applications where noise is unavoidable. The speech accuracy reduces strictly when the systems are operated in noisy environments. There are different Speech enhancement methods, a generalized form of Principal Component Analysis (PCA) is used for speech enhancement. A PCA based algorithm is proposed for denoising of speech degraded by noise interference. Principle Component Analysis (PCA) is a standard tool in modern data analysis because it is simple method for extracting relevant information from complex data matrix using eigenvalues and eigenvectors. By selecting conveniently the numbers of retained principal components, interesting simplified signals can be reconstructed.
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