Dysphonic speech analysis using generalized variogram

Acoustic analyses of speech signals are popular in the framework of the clinical evaluation of voice and the diagnosis of disease. We propose a new strategy for dysphonic speech analysis that extracts vocal dysperiocities by using a generalized form of the variogram. The generalized variogram allows the inherent drawbacks of both long-term and short-term linear prediction formulations, widely used in disordered speech analysis, to be overcome. The proposed approach uses a forgetting factor to account for the nonstationarity nature of the speech signal. Experimental results show that the proposed approach outperforms the double prediction-based technique.