Abstract
The article concerns methodological problems posed by multi-step predictive analysis of speech, carried out with a view to estimating vocal dysperiodicities. Problems that are discussed are the following. First, the stability of the multi-step predictive synthesis filter; second, the decrease of quantization noise by means of multiple prediction coefficients; third, the implementation of multi-step predictive analyses via lattice filters; fourth, the adequacy per se of the multi-step predictive analysis paradigm for estimating vocal dysperiodicities. Results suggest that implementations of multi-step predictive analyses that are considered to be optimal for speech coding are sub-optimal for clinical applications and vice versa. Also, multi-step predictive analyses as such do not appear to be under all circumstances a paradigm adequate for analysing vocal dysperiodicities unambiguously. An alternative is discussed, which is based on a generalized variogram of the speech signal.
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Schoentgen, J., Dessalle, E., Kacha, A., Grenez, F. (2006). Issues in Clinical Applications of Bilateral Multi-step Predictive Analysis of Speech. In: Faundez-Zanuy, M., Janer, L., Esposito, A., Satue-Villar, A., Roure, J., Espinosa-Duro, V. (eds) Nonlinear Analyses and Algorithms for Speech Processing. NOLISP 2005. Lecture Notes in Computer Science(), vol 3817. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11613107_17
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DOI: https://doi.org/10.1007/11613107_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-31257-4
Online ISBN: 978-3-540-32586-4
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