On the empirical mode decomposition in time-frequency representation of audio signals considering disjoint orthogonality

Abstract

Summary form only given. Empirical mode decomposition (EMD) is an adaptive process to decompose a non-stationary and nonlinear signal into the oscillating components. The EMD together with Hilbert transformation produces the Hilbert spectrum (HS), a fine-resolution time-frequency representation of non-stationary signals. Time-frequency representation is used in many signal-processing techniques, including separation of mixed audio signals. In this paper, we have presented the disjoint orthogonal property of audio signals as the decisive factor to measure the efficiency of the time-frequency representation. Some audio sources are considered as disjoint orthogonal if not more than one source is active at any time-frequency point. The audio signals are projected onto the time-frequency plane using HS and short-time Fourier spectrum and the quantitative measures of disjoint orthogonality with both of the methods are compared. The experimental results show that the HS based method performs better in time-frequency representation of the audio signals with the consideration of disjoint orthogonality.