Online Noisy Single-Channel Source Separation Using Adaptive Spectrum Amplitude Estimator and Masking

Tengtrairat, N., Woo, Wai Lok, Dlay, Satnam and Gao, Bin (2016) Online Noisy Single-Channel Source Separation Using Adaptive Spectrum Amplitude Estimator and Masking. IEEE Transactions on Signal Processing, 64 (7). pp. 1881-1895. ISSN 1053-587X

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A novel single-channel source separation method is presented to recover the original signals given only a single observed mixture in noisy environment. The proposed separation method is an online adaptive process and independent of parameters initialization. In this paper, a noisy pseudo-stereo mixing model is developed by formulating an artificial mixture from the observed mixture where the signals are modeled by the autoregressive process. The proposed demixing process composes of two steps: First, the noisy mixing model is enhanced by selecting the time-frequency (TF) units of signal presence and computing the mixture spectral amplitude, and second, an adaptive estimation of the parameters associated with each source is computed frame-by-frame, which is then used to construct a TF mask for the separation process. To assess the performance of the proposed method, noisy mixtures of real-audio sources with nonstationary noise have been conducted under various SNRs. Experiments show that the proposed algorithm has yielded superior separation performance especially in low input SNR compared with existing methods.

Item Type: Article
Uncontrolled Keywords: Blind source separation, masking, noise reduction, single-channel separation, underdetermined mixture
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 05 Apr 2019 13:58
Last Modified: 17 Nov 2020 12:15

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