Volume 10, Number 4 (Dec 2014 2014)                   IJEEE 2014, 10(4): 256-266 | Back to browse issues page


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Geravanchizadeh M, Ghalami Osgouei S. Speech Enhancement by Modified Convex Combination of Fractional Adaptive Filtering. IJEEE. 2014; 10 (4) :256-266
URL: http://ijeee.iust.ac.ir/article-1-659-en.html

Abstract:   (1513 Views)
This paper presents new adaptive filtering techniques used in speech enhancement system. Adaptive filtering schemes are subjected to different trade-offs regarding their steady-state misadjustment, speed of convergence, and tracking performance. Fractional Least-Mean-Square (FLMS) is a new adaptive algorithm which has better performance than the conventional LMS algorithm. Normalization of LMS leads to better performance of adaptive filter. Furthermore, convex combination of two adaptive filters improves its performance. In this paper, new convex combinational adaptive filtering methods in the framework of speech enhancement system are proposed. The proposed methods utilize the idea of normalization and fractional derivative, both in the design of different convex mixing strategies and their related component filters. To assess our proposed methods, simulation results of different LMS-based algorithms based on their convergence behavior (i.e., MSE plots) and different objective and subjective criteria are compared. The objective and subjective evaluations include examining the results of SNR improvement, PESQ test, and listening tests for dual-channel speech enhancement. The powerful aspects of proposed methods are their low complexity, as expected with all LMS-based methods, along with a high convergence rate.
Full-Text [PDF 436 kb]   (1078 Downloads)    
Type of Study: Research Paper | Subject: Speech Processing
Received: 2013/12/14 | Accepted: 2014/12/24 | Published: 2014/12/24

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