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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...
This paper presents a method of audio signal separation from stereo mixtures using binary masking in time-frequency (TF) domain based on the spatial location of the audio sources. The TF representation of audio signal is obtained by Hubert spectrum (HS). The Hubert transformation together with empirical mode decomposition (EMD) produces HS which is a fine-resolution TF representation of any nonlinear...
In this paper, a localization based approach of audio signal separation from binary mixtures is carried out. The audio sources are localized in the spatial domain (azimuth plane) using the delay and amplitude variation cues between two microphones' signals. A coherence based technique is introduced here to localize the audio sources in adverse acoustical environment. The mixture signals are decomposed...
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