Description: Robust Adaptation to Non-Native Accents in Automatic Speech Recognition by Silke Goronzy Furthermore, a specific pronunciation modelling technique that allows the automatic derivation of non-native pronunciations without using non-native data is described and combined with the previous techniques to produce a robust adaptation to non-native accents in an automatic speech recognition system. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description Speech recognition technology is being increasingly employed in human-machine interfaces. A remaining problem however is the robustness of this technology to non-native accents, which still cause considerable difficulties for current systems.In this book, methods to overcome this problem are described. A speaker adaptation algorithm that is capable of adapting to the current speaker with just a few words of speaker-specific data based on the MLLR principle is developed and combined with confidence measures that focus on phone durations as well as on acoustic features. Furthermore, a specific pronunciation modelling technique that allows the automatic derivation of non-native pronunciations without using non-native data is described and combined with the previous techniques to produce a robust adaptation to non-native accents in an automatic speech recognition system. Notes Springer Book Archives Table of Contents ASR:AnOverview.- Pre-processing of the Speech Data.- Stochastic Modelling of Speech.- Knowledge Bases of an ASR System.- Speaker Adaptation.- Confidence Measures.- Pronunciation Adaptation.- Future Work.- Summary.- Databases and Experimental Settings.- MLLR Results.- Phoneme Inventory. Promotional Springer Book Archives Long Description Speech recognition technology is being increasingly employed in human-machine interfaces. A remaining problem however is the robustness of this technology to non-native accents, which still cause considerable difficulties for current systems. In this book, methods to overcome this problem are described. A speaker adaptation algorithm that is capable of adapting to the current speaker with just a few words of speaker-specific data based on the MLLR principle is developed and combined with confidence measures that focus on phone durations as well as on acoustic features. Furthermore, a specific pronunciation modelling technique that allows the automatic derivation of non-native pronunciations without using non-native data is described and combined with the previous techniques to produce a robust adaptation to non-native accents in an automatic speech recognition system. Feature Includes supplementary material: sn.pub/extras Details ISBN3540003258 Author Silke Goronzy Short Title ROBUST ADAPTATION TO NON-NATIV Language English ISBN-10 3540003258 ISBN-13 9783540003250 Media Book Format Paperback DEWEY 006.454 Series Number 2560 Imprint Springer-Verlag Berlin and Heidelberg GmbH & Co. K Place of Publication Berlin Country of Publication Germany Pages 146 Illustrations XI, 146 p. DOI 10.1007/b83553;10.1007/3-540-36290-8 Publisher Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Edition Description 2002 ed. Year 2002 Edition 2002nd Publication Date 2002-12-19 Audience Postgraduate, Research & Scholarly Series Lecture Notes in Computer Science We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:137847223;
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ISBN-13: 9783540003250
Book Title: Robust Adaptation to Non-Native Accents in Automatic Speech Recog
Number of Pages: 146 Pages
Language: English
Publication Name: Robust Adaptation to Non-Native Accents in Automatic Speech Recognition
Publisher: Springer-Verlag Berlin and Heidelberg Gmbh & Co. Kg
Publication Year: 2002
Subject: Engineering & Technology, Computer Science
Item Height: 235 mm
Item Weight: 530 g
Type: Textbook
Author: Silke Goronzy
Item Width: 155 mm
Format: Paperback
