Robust Adaptation to Non-Native Accents
โ Silke Goronzy (eds.)
๐ Library
๐
2002
๐ Springer
๐ English
โฆ LIBER โฆ
๐
Robust Adaptation to Non-Native Accents in Automatic Speech Recognition
โ Scribed by Silke Goronzy (eds.)
- Publisher
- Springer-Verlag Berlin Heidelberg
- Year
- 2002
- Tongue
- English
- Leaves
- 134
- Series
- Lecture Notes in Computer Science 2560 : Lecture Notes in Artificial Intelligence
- Edition
- 1
- Category
- Library
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โฆ Synopsis
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.
โฆ Table of Contents
Introduction....Pages 1-5
ASR:AnOverview....Pages 7-13
Pre-processing of the Speech Data....Pages 15-19
Stochastic Modelling of Speech....Pages 21-29
Knowledge Bases of an ASR System....Pages 31-36
Speaker Adaptation....Pages 37-56
Confidence Measures....Pages 57-78
Pronunciation Adaptation....Pages 79-104
Future Work....Pages 105-107
Summary....Pages 109-112
Databases and Experimental Settings....Pages 131-134
MLLR Results....Pages 135-138
Phoneme Inventory....Pages 139-144
โฆ Subjects
Artificial Intelligence (incl. Robotics); Mathematical Logic and Formal Languages; User Interfaces and Human Computer Interaction
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