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Robust Digital Processing of Speech Signals [electronic resource] / by Branko Kovacevic, Milan M. Milosavljevic, Mladen Veinović, Milan Marković.

By: Contributor(s): Material type: TextTextPublisher: Cham : Springer International Publishing : Imprint: Springer, 2017Description: XII, 224 p. 54 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319536132
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 621.382 23
Online resources:
Contents:
Modelling of Speech Signal -- Review of Standard Methods -- Fundamentals of Robust Parameter Estimation -- Robust Nonrecursive AR Analysis of Speech Signals -- Robust Recursive AR Analysis of Speech Signals -- Robust Estimation Based on Pattern Recognition -- Application of Robust Estimators in Speech Signal Processing.
In: Springer eBooksSummary: This book focuses on speech signal phenomena, presenting a robustification of the usual speech generation models with regard to the presumed types of excitation signals, which is equivalent to the introduction of a class of nonlinear models and the corresponding criterion functions for parameter estimation. Compared to the general class of nonlinear models, such as various neural networks, these models possess good properties of controlled complexity, the option of working in "online" mode, as well as a low information volume for efficient speech encoding and transmission. Providing comprehensive insights, the book is based on the authors' research, which has already been published, supplemented by additional texts discussing general considerations of speech modeling, linear predictive analysis and robust parameter estimation.
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Modelling of Speech Signal -- Review of Standard Methods -- Fundamentals of Robust Parameter Estimation -- Robust Nonrecursive AR Analysis of Speech Signals -- Robust Recursive AR Analysis of Speech Signals -- Robust Estimation Based on Pattern Recognition -- Application of Robust Estimators in Speech Signal Processing.

This book focuses on speech signal phenomena, presenting a robustification of the usual speech generation models with regard to the presumed types of excitation signals, which is equivalent to the introduction of a class of nonlinear models and the corresponding criterion functions for parameter estimation. Compared to the general class of nonlinear models, such as various neural networks, these models possess good properties of controlled complexity, the option of working in "online" mode, as well as a low information volume for efficient speech encoding and transmission. Providing comprehensive insights, the book is based on the authors' research, which has already been published, supplemented by additional texts discussing general considerations of speech modeling, linear predictive analysis and robust parameter estimation.