书目名称 | Robust Adaptation to Non-Native Accents in Automatic Speech Recognition |
编辑 | Silke Goronzy |
视频video | |
概述 | Includes supplementary material: |
丛书名称 | Lecture Notes in Computer Science |
图书封面 |  |
描述 | .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.. |
出版日期 | Book 2002 |
关键词 | Automat; Automatic Speech Recognition; Confidence Measures; Human-Machine Interfaces; MLLR; Natural Langu |
版次 | 1 |
doi | https://doi.org/10.1007/3-540-36290-8 |
isbn_softcover | 978-3-540-00325-0 |
isbn_ebook | 978-3-540-36290-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 |
issn_series | 0302-9743 |
copyright | Springer-Verlag Berlin Heidelberg 2002 |