Empirical mode decomposition of voiced speech signal

Abstract

This paper describes a new technique, called the empirical mode decomposition (EMD) that has recently been pioneered by N. E. Huang and al., for adaptively representing nonstationary signals as sums of zero-mean AM-FM components [N. E. Huang, et al., 1998]. The components, called intrinsic mode functions (IMFs), allow the analysis of frequency composition of one-dimensional signals. Applied to speech signal, the EMD allows us to study the different intrinsic oscillatory modes. Besides, computing the LPC analysis of each mode provides an estimation of formants. The presented method is firstly applied on a sum of pure frequency signals. Among different modes we can detect all frequencies taking a part of a signal.