J93-3001 significant progress in message understanding technology . This level of progress raises
W10-4152 Introduction Incorporating semantic understanding technologies from the field of NLP becomes
W98-0205 speech , and natural-language understanding technology can we successfully populate
W01-1009 parser itself . As natural language understanding technology improves , we can use more and
P03-1033 recognition and natural language understanding technologies . A typical task of spoken dialogue
W01-1602 the underlying spoken language understanding technology itself . Applications are specified
H94-1103 speech recognition and language understanding technologies for large vocabulary spoken langauge
H01-1073 synthesis and natural language understanding technologies using the DARPA Hub Architecture
A92-1024 Conclusions JASPER shows that text understanding technology has progressed to the point that
H91-1059 of or in concert with language understanding technology . The inputs to the analysis/extraction
W03-2704 ViaVoiceTM and Natural Language Understanding technology . The NLU client of PGIS can
W07-0312 intelligence through spoken language understanding technology called WIRE or Wearable Intelligent
H94-1084 addition , natural languag , . understanding technology call be used to imprt , ve tilt
I05-4001 natural language partial parsing and understanding technology combining statistic technology
H89-2077 development of a mature natural language understanding technology . The speech recognition problem
W15-4629 speech recognition and language understanding technology to identify appropriate responses
N09-4006 allowing a new generation of language understanding technologies to be developed with new functional
M95-1001 internal evaluations . Language understanding technology might develop in ways very different
H92-1095 applying general-purpose language understanding technology to spoken language understanding
H94-1011 Consortium ( LDC ) . Spoken language understanding technology tests made use of ARPA Air Travel
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