Robustness in Language and Speech Technology

1. Auflage. Softcover version of original hardcover Auflage 2001
ISBN: 978-90-481-5643-6
Verlag: Springer

Buch, Englisch, 278 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 446 g

Reihe: Text, Speech and Language Technology

In this book we address 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. This 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.
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.

Zielgruppe

Research

Autoren/Hrsg.

Junqua, Jean-Claude

Noord, Gertjan Van

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
• Mathematik | Informatik EDV | Informatik Informatik Natürliche Sprachen & Maschinelle Übersetzung
• Geisteswissenschaften Sprachwissenschaft Sprachwissenschaften
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Geisteswissenschaften Sprachwissenschaft Computerlinguistik, Korpuslinguistik

Inhaltsverzeichnis

1 Introduction.- 2 Acoustic Features and Distance Measure.- 3 Speaker Compensation in Automatic Speech Recogniton.- 4 Robustness in Statistical Language Modeling.- 5 Improving Robustness by Modeling Spontaneous Speech Events.- 6 Regular Approximation of Context-Free Grammars.- 7 Weighted Grammar Tools: the GRM Library.- 8 Robust Parsing and Beyond.- 9 Robust Parsing of Word Graphs.- 10 Balancing Robustness and Efficiency.