Wolfgang Minker, Alex Waibel, Joseph Mariani

Stochastically-Based Semantic Analysis

• Gebundenes Buch

Produktbeschreibung

Stochastically-Based Semantic Analysis investigates the problem of automatic natural language understanding in a spoken language dialog system. The focus is on the design of a stochastic parser and its evaluation with respect to a conventional rule-based method.
Stochastically-Based Semantic Analysis will be of most interest to researchers in artificial intelligence, especially those in natural language processing, computational linguistics, and speech recognition. It will also appeal to practicing engineers who work in the area of interactive speech systems.

Produktdetails

• The Springer International Series in Engineering and Computer Science 514
• Verlag: Springer / Springer US / Springer, Berlin
• Artikelnr. des Verlages: 978-0-7923-8571-4
• 1999.
• Seitenzahl: 244
• Erscheinungstermin: 31. August 1999
• Englisch
• Abmessung: 241mm x 160mm x 18mm
• Gewicht: 522g
• ISBN-13: 9780792385714
• ISBN-10: 0792385713
• Artikelnr.: 22924060

Inhaltsangabe

1. Introduction.- 2. Research Framework.- 3. Applications and Corpora.- 4. Portability of a Rule-Based Case Frame Parser.- 5. Stochastically-Based Case Frame Parser.- 6. Portability of the Stochastic Parser.- 7. Summary of Results.- 8. Conclusion.- Appendices.- A- Rule-based Language Porting.- B- Case Values in French and English.- C- System Query Language for L'ATIS.- D- Test Subsets.- E- Commonly-used Abbreviations.- F- Utterance References.- References.

Rezensionen

`Altogether the book is well worth reading. The research reported in this book is very interesting, and the authors managed to almost find the right level of detail in their descriptions, enabling the reader to understand how a system works without losing the overall picture.' Natural Language Engineering, 7:1 (2001)

`Altogether the book is well worth reading. The research reported in this book is very interesting, and the authors managed to almost find the right level of detail in their descriptions, enabling the reader to understand how a system works without losing the overall picture.'
Natural Language Engineering, 7:1 (2001)