Speech enhancement using posterior regularized NMF with bases update. (August 2017)

• Record Type: Journal Article
• Authors: Sunnydayal, V.; Kishore kumar, T.
• Is Part Of: Computers & electrical engineering. Volume 62(2017)
• Page Start: 663
• Page End: 675
• Publication Date: 2017-08
• Subjects: Non-negative matrix factorization -- On-line bases update -- Statistical model-based enhancement -- Posterior regularization; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2017.02.021
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: In this paper, a combination of statistical model-based approach and Non-negative Matrix Factorization (NMF)-based approach with on-line update of speech and noise bases for speech enhancement is proposed. Template-based approaches are more robust and perform better than non-stationary noises compared to statistical model-based approaches but are dependent on a priori information. Combining the approaches avoids the drawbacks of both. To improve the performance further, speech and noise bases are adapted simultaneously in NMF approach with the help of the estimated speech presence probability (SPP). The proposed method outperforms other benchmark algorithms in terms of perceptual evaluation of speech quality (PESQ) and source-to-distortion ratio (SDR) in stationary and non-stationary noise environment conditions with matched and mismatched noise basis.