| T87-1027 | several questions for theories of | natural-language understanding | . First , how do people get away |
| W98-0205 | interaction of image , speech , and | natural-language understanding | technology can we successfully |
| W94-0114 | fewer rules than one for full | natural-language understanding | . Creating the full synonym list |
| J88-2011 | textbook about the use of Prolog for | natural-language understanding | . I feel that this well-written |
| J06-2004 | i.e. , speech recognition and | natural-language understanding | ) was performed by a human . |
| H94-1115 | 18.2 % utterance error on the | natural-language understanding | task , and 20.7 % utterance error |
| M95-1019 | state technologies in constrained | natural-language understanding | tasks . The system has undergon |
| P85-1022 | feature of computer systems for | natural-language understanding | , and one • which is shared |
| H93-1108 | improved from 31.1 % to 23.6 % in the | natural-language understanding | test , and from 45.4 % to 33.2 |
| M93-1022 | be viewed as abduction . NUBA ( | Natural-language Understanding | By Abduction ) is a natural language |
| P87-1004 | analyzer is designed with the goal of | natural-language understanding | in mind ; therefore , object |
| W94-0114 | retrieval does not require the full | natural-language understanding | that hand-tailored semantic routines |
| J79-1021 | in the design of software for " | natural-language understanding | " is to deal with ( a ) a specialized |
| P84-1094 | knowledge base shall be whether | natural-language understanding | problems demonstrate the need |
| J88-2001 | being used in the JANUS system , a | natural-language understanding | and generation system under joint |
| P01-1057 | While many speech recognition and | natural-language understanding | applications can be tested by |
| C92-3147 | significant problems found in | natural-language understanding | . However , these thearies offer |
| J88-3016 | central to computational theories of | natural-language understanding | ( cf. Rapaport 1987 ) . The fifth |
| H92-1006 | MIT 's TINA \ -LSB- 15 \ -RSB- | natural-language understanding | system and then to M1T software |
| J88-3016 | cognitive science and computational | natural-language understanding | , where it is essential to recognize |
