Microphone wind noise reduction using singular spectrum analysis techniques

Eldwaik, O and Li, FF 2017, Microphone wind noise reduction using singular spectrum analysis techniques , in: 33nd Annual Conference And Exhibition. Reproduced Sound 2017 : Sound Quality By Design, 21-23 November 2017, Nottingham, UK.

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Abstract

Wind noise is a known problem that contaminates microphone signals in many field measurement and audio recording scenarios. A recently completed EPSRC project has led to the development of a tool to detect such noise; this paper takes a step further by proposing the use of singular spectrum analysis (SSA) techniques to reduce such noise. One of the advantages of the SSA method is that it has the potential to retain wanted signals with less distortions when compared with other known signal processing techniques for wind noise reduction. The SSA decomposes signals in eigen-spaces, selects and groups the principal components according to their contributions and eventually reconstructs the wanted components back to the time domain. Following a brief review of the wind noise problem and existing solutions, this paper outlines the principle of SSA method, discusses group techniques used in the SSA procedures for wind noise removal, and presents the results.

Item Type: Conference or Workshop Item (Paper)
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Proceedings of the Institute of Acoustics, Vol. 39 Pt. 1
Publisher: Institute of Acoustics
Related URLs:
Depositing User: Omar Eldwaik
Date Deposited: 02 Jan 2018 12:58
Last Modified: 02 Jan 2018 16:01
URI: http://usir.salford.ac.uk/id/eprint/44787

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