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.
表中的内容
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.
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