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Language modeling for automatic spee...

Donaj, Gregor.

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Language modeling for automatic speech recognition of inflective languages = an applications-oriented approach using lexical data /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Language modeling for automatic speech recognition of inflective languages/ by Gregor Donaj, Zdravko Kacic.
Reminder of title:	an applications-oriented approach using lexical data /
Author:	Donaj, Gregor.
other author:	Kacic, Zdravko.
Published:	Cham :Springer International Publishing : : 2017.,
Description:	viii, 71 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Speech Recognition in Inflective Languages -- Performance Evaluation Using Lexical Data -- Application Oriented Language Modeling -- An Example Application -- Conclusion.
Contained By:	Springer eBooks
Subject:	Automatic speech recognition. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-41607-6
ISBN:	9783319416076

Language modeling for automatic speech recognition of inflective languages = an applications-oriented approach using lexical data /
Donaj, Gregor.

Language modeling for automatic speech recognition of inflective languagesan applications-oriented approach using lexical data /[electronic resource] :by Gregor Donaj, Zdravko Kacic. - Cham :Springer International Publishing :2017. - viii, 71 p. :ill., digital ;24 cm. - SpringerBriefs in electrical and computer engineering, Speech technology,2191-8112. - SpringerBriefs in electrical and computer engineering.Speech technology..

Introduction -- Speech Recognition in Inflective Languages -- Performance Evaluation Using Lexical Data -- Application Oriented Language Modeling -- An Example Application -- Conclusion.

This book covers language modeling and automatic speech recognition for inflective languages (e.g. Slavic languages), which represent roughly half of the languages spoken in Europe. These languages do not perform as well as English in speech recognition systems and it is therefore harder to develop an application with sufficient quality for the end user. The authors describe the most important language features for the development of a speech recognition system. This is then presented through the analysis of errors in the system and the development of language models and their inclusion in speech recognition systems, which specifically address the errors that are relevant for targeted applications. The error analysis is done with regard to morphological characteristics of the word in the recognized sentences. The book is oriented towards speech recognition with large vocabularies and continuous and even spontaneous speech. Today such applications work with a rather small number of languages compared to the number of spoken languages. Concentrates on speech recognition for inflective languages - representative of roughly half of Europe -- and their unique characteristics Introduces new application-oriented methods for measuring the performance of a speech recognition system Presents examples of language modeling to maximize the performance of a speech recognition system Provides techniques for analyzing errors and identifying their sources in a speech recognition system from a lexical point of view rather than acoustic point of view.

ISBN: 9783319416076

Standard No.: 10.1007/978-3-319-41607-6doiSubjects--Topical Terms:

753709
Automatic speech recognition.

LC Class. No.: TK7895.S65

Dewey Class. No.: 006.454

Language modeling for automatic speech recognition of inflective languages = an applications-oriented approach using lexical data /
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505 0 $a Introduction -- Speech Recognition in Inflective Languages -- Performance Evaluation Using Lexical Data -- Application Oriented Language Modeling -- An Example Application -- Conclusion.
520 $a This book covers language modeling and automatic speech recognition for inflective languages (e.g. Slavic languages), which represent roughly half of the languages spoken in Europe. These languages do not perform as well as English in speech recognition systems and it is therefore harder to develop an application with sufficient quality for the end user. The authors describe the most important language features for the development of a speech recognition system. This is then presented through the analysis of errors in the system and the development of language models and their inclusion in speech recognition systems, which specifically address the errors that are relevant for targeted applications. The error analysis is done with regard to morphological characteristics of the word in the recognized sentences. The book is oriented towards speech recognition with large vocabularies and continuous and even spontaneous speech. Today such applications work with a rather small number of languages compared to the number of spoken languages. Concentrates on speech recognition for inflective languages - representative of roughly half of Europe -- and their unique characteristics Introduces new application-oriented methods for measuring the performance of a speech recognition system Presents examples of language modeling to maximize the performance of a speech recognition system Provides techniques for analyzing errors and identifying their sources in a speech recognition system from a lexical point of view rather than acoustic point of view.
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