Abstract
In this paper, we define an algorithm with low complexity which performs a new use of the linear prediction analysis (covariance method) to retrieve the maximum-phase component of speech signals. First, we study the mixed-phase model of speech through a new representation named the Zeros of Z-Transform (ZZT) in the z-plane, which is an all-zero representation of the z-transform of a discrete time signal. Then, based on the properties of the mixed-phase model, we introduce an algorithm to estimate the anticausal glottal flow component from speech signals. LP-covariance analysis is used to estimate a pole pair outside the unit circle corresponding to the anticausal poles of the source signal component in the mixed-phase speech model. Given the pair of anticausal poles, a procedure to resynthesize the anticausal part of the glottal flow, and then an open quotient estimation method, are proposed. Evaluations show that the method is high quality for analyzing synthetic speech but lacks robustness in analysis of natural speech.
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© 2005 Springer-Verlag Berlin Heidelberg
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Bozkurt, B., Severin, F., Dutoit, T. (2005). An Algorithm to Estimate Anticausal Glottal Flow Component from Speech Signals. In: Chollet, G., Esposito, A., Faundez-Zanuy, M., Marinaro, M. (eds) Nonlinear Speech Modeling and Applications. NN 2004. Lecture Notes in Computer Science(), vol 3445. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11520153_15
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DOI: https://doi.org/10.1007/11520153_15
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