DocumentCode :
312151
Title :
Language understanding using hidden understanding models
Author :
Schwartz, Richard ; Miller, Scott ; Stallard, David ; Makhoul, John
Author_Institution :
BBN Syst. & Technol. Corp., Cambridge, MA, USA
Volume :
2
fYear :
1996
fDate :
3-6 Oct 1996
Firstpage :
997
Abstract :
Describes a sentence understanding system that is completely based on learned methods both for understanding individual sentences and for determining their meaning in the context of the preceding sentences. We describe the models used for each of three stages in the understanding: semantic parsing, semantic classification and discourse modeling. When we ran this system on the December 1994 test of the ARPA Air Travel Information System (ATIS) task, we achieved a 14.5% error rate. The error rate for those sentences that are context-independent (class A) was 9.5%
Keywords :
natural languages; pattern classification; public information systems; speech recognition; travel industry; ARPA Air Travel Information System; ATIS task; class A sentences; context-independent sentences; discourse modeling; error rate; hidden understanding models; language understanding; learned methods; semantic classification; semantic parsing; sentence meaning determination; sentence understanding system; Error analysis; Hidden Markov models; Information systems; Natural languages; Probability; Radio access networks; Robustness; Speech recognition; System testing; Tagging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-7803-3555-4
Type :
conf
DOI :
10.1109/ICSLP.1996.607771
Filename :
607771
Link To Document :
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