Time-frequency representation of audio signals using Hilbert spectrum with effective frequency scaling

The efficiency of Hilbert spectrum (HS) in time-frequency representation (TFR) of audio signals is investigated in this paper. HS is derived by applying empirical mode decomposition (EMD), a newly developed data adaptive method for nonlinear and non-stationary signal analysis together with Hilbert transform. EMD represents any time domain signal as a sum of a finite number of bases called intrinsic mode functions (IMFs). The instantaneous frequency responses of the IMFs derived through Hilbert transform are arranged to obtain the TFR of the analyzing signal yielding the HS. A new frequency scaling method is introduced here for proper interpretation of the energy spectra in HS. The performance of HS is compared with well known and widely used short-time Fourier transform (STFT) technique for TFR. The experimental results show that HS based method performs better than STFT in time-frequency representation of the audio signals.