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Robustness in Language and Speech Processing
Sold out, available from Springer
edited by Jean-Claude Junqua and Gertjan van Noord
This book addresses robustness issues at the speech
recognition and natural language parsing levels, with a focus on
feature extraction and noise robust recognition, adaptive
systems, language modeling, parsing, and natural language
understanding. The book attempts to give a clear overview of the
main technologies used in language and speech processing, along
with an extensive bibliography to enable topics of interest to be
pursued further. It also brings together speech and language
technologies often considered separately.
Robustness in Language and Speech Technology serves as a valuable
reference and although not intended as a formal university
textbook, contains some material that can be used for a course at
the graduate or undergraduate level.
- Introduction; J.-C. Junqua, G. van Noord.
- Acoustic Features and Distance Measure; J. de Veth, et al.
- Speaker Compensation in Automatic Speech Recognition; D.T. Merino.
- Robustness in Statistical Language Modeling; J.R. Bellegarda.
- Improving Robustness by Modeling Spontaneous Speech Events; P.A. Heeman, J.F. Allen.
- Regular Approximation of Context-Free Grammars; M. Mohri, M.-J. Nederhof.
- Weighted Grammer Tools: The GRM Library; M. Mohri.
- Robust Parsing and Beyond; J.-P. Chanod.
- Robust Parsing of Word Graphs; G. van Noord.
- Balancing Robustness and Efficiency; C.Penstein Rosť, A. Lavie.
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