PCA based Single Channel Speech Enhancement Method for Highly Noisy Environment

被引：0
|
作者：
Bavkar, Sangita [1 ]
Sahare, Shashikant [2 ]
机构：
[1] PVGs Coll Engn & Technol, Pune, Maharashtra, India
[2] Cummins Coll Engn Women, Elect & Telecommun, Pune, Maharashtra, India
来源：
2013 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI) | 2013年
关键词：
Speech Enhancement; Subspace Approach; Principal Component Analysis (PCA); Eigenvalue Decomposition; Noise Variance;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页码：1103 / 1107
页数：5
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