By Topic

A stochastic case frame approach for natural language understanding

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Minker, W. ; Lab. d''Informatique pour la Mecanique et les Sci. de l''Ingenieur, CNRS, Orsay, France ; Bennacef, S. ; Gauvain, J.

A stochastically based approach for the semantic analysis component of a natural spoken language system for the ARPA Air Travel Information Services (ATIS) task has been developed. The semantic analyzer of the spoken language system already in use at LIMSI makes use of a rule-based case grammar. In this work, the system of rules for the semantic analysis is replaced with a relatively simple first-order hidden Markov model. The performances of the two approaches can be compared because they use identical semantic representations, despite their rather different methods for meaning extraction. We use an evaluation methodology that assesses performance at different semantic levels, including the database response comparison used in the ARPA ATIS paradigm

Published in:

Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on  (Volume:2 )

Date of Conference:

3-6 Oct 1996