TITLE

An Improved Monaural Speech Enhancement Algorithm Based on Sparse Dictionary Learning

AUTHOR(S)
LI Yi-nan; ZHANG Xiong-wei; ZENG Li; HUANG Jian-jun
PUB. DATE
January 2014
SOURCE
Journal of Signal Processing;Jan2014, Vol. 30 Issue 1, p44
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
This paper applies the K-Singular Value Decomposition method and its non-negative variant to enhance the contaminated speech. In the proposed approach, noise is categorized as structured and unstructured noise. Firstly, the noise dictionary is learned from a training noise database. Then, we remove the structured noise iteratively by using the noise dictionary. Finally the approach adopts spars and redundant representations over trained dictionary to separate the clean speech from the unstructured noise. Extensive experimental results show that the enhancement method proposed outperforms state-of-the-art methods like multi-band spectral subtraction and the non-negative sparse coding based noise reduction algorithm.
ACCESSION #
94755426

 

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