Title : 
PCA based single channel speech enhancement method for highly noisy environment
         
        
            Author : 
Bavkar, Sangita ; Sahare, Shashikant
         
        
            Author_Institution : 
Electron. & Telecommun., Coll. of Eng. & Technol., Pune, India
         
        
        
        
        
            Abstract : 
In this paper, we proposed speech enhancement method using principal component analysis (PCA) for noisy signal. This algorithm is based on the PCA which is subspace approach. Subspace method separates the signal and noise subspace using eigenvalue analysis. Improved signal can be reconstructed by removing the noise subspace and retaining the signal subspace by selecting suitably the number of principal components. In this paper the experimental results shows the good noise reduction with minimum signal distortion.
         
        
            Keywords : 
eigenvalues and eigenfunctions; principal component analysis; speech enhancement; PCA based single channel speech enhancement method; eigenvalue analysis; highly noisy environment; minimum signal distortion; noise subspace separation; noisy signal; principal component analysis; principal components; signal subspace separation; subspace method; Covariance matrices; Noise measurement; Principal component analysis; Signal to noise ratio; Speech; Speech enhancement; Eigenvalue Decomposition; Noise Variance; Principal Component Analysis (PCA); Speech Enhancement; Subspace Approach;
         
        
        
        
            Conference_Titel : 
Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on
         
        
            Conference_Location : 
Mysore
         
        
            Print_ISBN : 
978-1-4799-2432-5
         
        
        
            DOI : 
10.1109/ICACCI.2013.6637331