H89-1010 using the standard 1000-word DARPA Resource Management Database \ -LSB- 8 \ -RSB- .
H89-1007 was evaluated using the DARPA Resource Management database . For the language modeling
H89-1005 with respect to the strict DARPA resource management task grammar . This is a finite
A94-1022 demonstration system in an Air Force Resource Management domain . We discuss results of
H89-1010 speaker-independent portion of the Resource Management Database . Two different training
C90-3100 problem of conflict resolution and resource management . The current a ` end in AI is
E09-3002 operations , are utilized for ease of resource management . As a result , CCG-MM is more
H89-1011 results conducted on the DARPA Resource Management database . 1 . Introduction Soon
E09-3002 decomposition rule and improve the ease of resource management in parallel . The memory mechanism
H89-1011 Experimental Results The DARPA Resource Management database \ -LSB- 4 \ -RSB- defines
H89-1012 system , we use the DARPA 1000-word Resource Management Database corpus . This corpus
E09-3002 showed that we can obtain a cleaner resource management in canonical CCG by the use of
E09-2006 Apart from the aspect of pure resource management , processing and analysis of
H89-1007 three speakers from the 1000word Resource Management database . The word accuracy
A00-2014 . 4 Evaluation Using the Naval Resource Management Domain An experiment was conducted
H89-1005 recognition of sentences from the DARPA resource management task are founded . The 51 states
A00-2014 Price et al. , 1988 ) and Extended Resource Management ( RM2 ) ( ( DARPA ) , 1990 )
H89-1006 system was tested on the DARPA Resource Management Database under several grammar
A00-2014 personnel familiar with naval resource management tasks . They were chosen for
H89-1016 corrective training . On the DARPA resource management task , SPHINX attained a speaker-independent
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