Cough sound recognition based on Hilbert marginal spectrum

Marginal spectrums of cough sound and non-cough sound are obtained through Hilbert-Huang Transform. Speech signals of cough sound and five different non-cough sounds, namely throat clearing, sigh voice, shouting voice, speech voice and laughter, are analyzed contrastively focusing on the characteristics of marginal spectrum. Then SECC is extracted for cough sound recognition. The paper mainly recognizes the characteristic parameters SECC and MFCC coefficient by using the Continuous Hidden Markov Model(CHMM). The recognition result shows that SECC parameter based on Hilbert marginal spectrum is more effective to distinguish the cough sound and non-cough sound.