Enhancing speech corrupted by nonstationary noise using nonnegative matrix factorization with multiple constraints
ZOU Yue-xian
LIU Shi-han
WANG Di-song
Abstract：The enhancement of speech corrupted by nonstationary noises under low signal-to-noise ratio (SNR) con-ditions is remaining open and still a very challenging task. To improve the traditional nonnegative matrix factorization (NMF) based speech enhancement, jointly taking the speech sparsity property in time-frequency domain and the low-rank property of nonstationary noise into account, a termed multi-constraint NMF speech enhancement method (MC–NMFSE) is developed. Essentially, in training stage, the speech and noise dictionaries have been constructed by using speech and noise training sets, respectively. In the speech enhancement stage, multi-constraint NMF method is adopted where the data matrix is factorized into two nonnegative sub-matrices with the sparsity and low rank constraints to guarantee the good rep-resentation of the speech components from their corrupted version by nonstationary noise. Compared with the traditional NMF speech enhancement method (NMF–SpEnM) and MC–NMFSE, intensive experiments under different nonstationary noise conditions and different signal-to-noise ratios have been carried out to evaluate their performance. Experimental results demonstrate that MC–NMFSE has lower speech distortion and better capability to suppress nonstationary noises.
Keywords：speech enhancementlow-ranksparsitynonnegative matrix factorizationnonstationary noise
Publication Date：2017-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：8( 761-768 )