Wind noise reduction using empirical mode decomposition

Abstract

One common problem of outdoor recordings is a contamination of wind noise which has highly non-stationary characteristics. Although there are a lot of noise reduction methods which work well for general kinds of noises, most methods perform worse for wind noise due to its non-stationary nature. Therefore, wind noise reduction need specific technique to overcome this non-stationarity. Empirical mode decomposition (EMD) is a relatively new method to decompose a signal into several data-driven bases which are modeled as amplitude and frequency modulated sinusoids that represent wind noise better than quasi-stationary analysis methods such as short-time Fourier transform since it assumes an analyzing signal as non-stationary. Thus, EMD has a potential to reduce wind noise from recorded sounds in an entirely different way from ordinary methods. In this paper, the method to apply EMD as a wind noise suppressor is presented. The experiment is performed on a female speech superimposed with wind noise, and the results showed its possibility.