ENGLISH

Robust Adaptation to Non-Native Accents in Automatic Speech Recognition

By Silke Goronzy (eds.)

Book information

Publisher
Springer-Verlag Berlin Heidelberg
Year
2002
ISBN
3540003258, 9783540003250
DOI
10.1007/3-540-36290-8
Open Library ID
OL17080512M
Language
english
Format
PDF
Filesize
1 MB (1157653 bytes)
Series
Lecture Notes in Computer Science 2560 : Lecture Notes in Artificial Intelligence
Edition
1
Pages
146\134
Library
Kolxo3
Time added
2011-01-23 12:00:00
Artificial Intelligence (incl. Robotics); Mathemat

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.

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