A Signal Subspace Speech Enhancement Approach Based on Joint Low-Rank and Sparse Matrix Decomposition

• Autorzy: Sun C. , Xie J. , Leng Y.

Identyfikatory

DOI

10.1515/aoa-2016-0024

• Języki publikacji: EN

Abstrakty

EN

Subspace-based methods have been effectively used to estimate enhanced speech from noisy speech samples. In the traditional subspace approaches, a critical step is splitting of two invariant subspaces associated with signal and noise via subspace decomposition, which is often performed by singular-value decomposition or eigenvalue decomposition. However, these decomposition algorithms are highly sensitive to the presence of large corruptions, resulting in a large amount of residual noise within enhanced speech in low signal-to-noise ratio (SNR) situations. In this paper, a joint low-rank and sparse matrix decomposition (JLSMD) based subspace method is proposed for speech enhancement. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank value for the underlying clean speech matrix. Then the subspace decomposition is performed by means of JLSMD, where the decomposed low-rank part corresponds to enhanced speech and the sparse part corresponds to noise signal, respectively. An extensive set of experiments have been carried out for both of white Gaussian noise and real-world noise. Experimental results show that the proposed method performs better than conventional methods in many types of strong noise conditions, in terms of yielding less residual noise and lower speech distortion.

Słowa kluczowe

EN

subspace speech enhancement; singular value decomposition; joint low-rank and sparse matrix decomposition

• Wydawca: Instytut Podstawowych Problemów Techniki PAN ; Komitet Akustyki PAN ; Polskie Towarzystwo Akustyczne
• Czasopismo: Archives of Acoustics
• Rocznik: 2016
• Tom: Vol. 41, No. 2
• Strony: 245--254
• Opis fizyczny: Bibliogr. 38 poz., rys., tab.

Twórcy

autor

Sun C.

• School of information, Nanchang Hangkong University, Nanchang, 330063, China
• Science and Technology on Avionics Integration Laboratory, Shanghai, China

autor

Xie J.

• School of information, Nanchang Hangkong University, Nanchang, 330063, China

autor

Leng Y.

• College of Physics and Electronics, Shandong Normal University, East Wenhua Road 88, 250014, Ji’nan, China

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Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.