Robust Digital Processing of Speech Signals [electronic resource] /

By:

Kovacevic, Branko [author.]

Contributor(s):

Language: ENG Publisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017Description: XII, 224 p. 54 illus. | Binding - Card Paper |Content type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783319536132

Subject(s):

Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:

621.382 23

Online resources:

Click here to access eBook in Springer Nature platform. (Within Campus only.)

In: Springer Nature eBookSummary: 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.

List(s) this item appears in: Springer Nature eBooks

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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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