| tech,13-2-C90-3014,bq | constructing a computational <term> phonological | system | </term> : <term> speech recognition </term> and | #16395 The approach of KPSG provides an explicit development model for constructing a computational phonological system: speech recognition and synthesis system. |
| accurately estimate the <term> confidence </term> the | system | has in the correctness of each <term> extracted | #6801 For many reasons, it is highly desirable to accurately estimate the confidence the system has in the correctness of each extracted field. | |
| measure(ment),7-2-H01-1068,bq | measure <term> user satisfaction </term> , <term> | system | support of mission success </term> and <term> | #1214 The three tiers measure user satisfaction,system support of mission success and component performance. |
| other,8-8-P05-1067,bq | system </term> outperforms the <term> baseline | system | </term> based on the <term> IBM models </term> | #9536 The result shows that our system outperforms the baseline system based on the IBM models in both translation speed and quality. |
| tool,7-1-H92-1016,bq | describes the status of the <term> MIT ATIS | system | </term> as of February 1992 , focusing especially | #18692 This paper describes the status of the MIT ATIS system as of February 1992, focusing especially on the changes made to the SUMMIT recognizer. |
| tech,15-3-P03-1033,bq | </term> : <term> skill level </term> to the <term> | system | </term> , <term> knowledge level </term> on the | #4337 Specifically, we set up three dimensions of user models: skill level to thesystem, knowledge level on the target domain and the degree of hastiness. |
| paper we present <term> ONTOSCORE </term> , a | system | for scoring sets of <term> concepts </term> | #2443 In this paper we present ONTOSCORE, a system for scoring sets of concepts on the basis of an ontology. | |
| lr,7-1-C90-3014,bq | <term> Korean phonological knowledge base | system | </term> using the <term> unification-based | #16366 This paper describes the framework of a Korean phonological knowledge base system using the unification-based grammar formalism: Korean Phonology Structure Grammar (KPSG). |
| tech,16-1-N03-3010,bq | language understanding </term> in a <term> dialogue | system | </term> . We build this based on both <term> | #3494 In this paper, we propose a novel Cooperative Model for natural language understanding in a dialogue system. |
| other,19-1-J88-3002,bq | they must have knowledge about the <term> | system | users </term> . This paper explores the role | #16034 For intelligent interactive systems to communicate with humans in a natural manner, they must have knowledge about thesystem users. |
| tech,7-3-C92-2115,bq | proposes a new type of </term><term> transfer | system | </term> , called a <term> Similarity-driven | #18117 This paper proposes a new type of transfer system, called a Similarity-driven Transfer System (SimTran), for use in such case-based MT (CBMT). |
| tech,41-3-C04-1035,bq | and <term> TiMBL </term> , a <term> memory-based | system | </term> . Both <term> learners </term> perform | #5224 We then use the predicates of such clauses to create a set of domain independent features to annotate an input dataset, and run two different machine learning algorithms: SLIPPER, a rule-based learning algorithm, and TiMBL, a memory-based system. |
| tech,1-2-C90-2032,bq | </term> of <term> sentences </term> . The <term> DoPS | system | </term> extracts preference knowledge from | #16306 The DoPS system extracts preference knowledge from a target document or other documents automatically. |
| tech,10-1-H01-1041,bq | <term> Korean-to-English machine translation | system | </term><term> CCLINC ( Common Coalition Language | #399 At MIT Lincoln Laboratory, we have been developing a Korean-to-English machine translation system CCLINC (Common Coalition Language System at Lincoln Laboratory). |
| tech,13-3-N06-2009,bq | paraphrasing technique </term> and evaluating <term> QA | system | </term> performance on <term> paraphrased questions | #10776 We investigate that claim by adopting a simple MT-based paraphrasing technique and evaluating QA system performance on paraphrased questions. |
| measure(ment),6-3-H05-1117,bq | automatic <term> methods </term> for <term> scoring | system | output </term> is an impediment to progress | #7577 The lack of automatic methods for scoring system output is an impediment to progress in the field, which we address with this work. |
| tool,22-9-I05-2048,bq | currently used as the basis of <term> CMU 's SMT | system | </term> . It has also successfully been coupled | #8166 STTK has been developed by the presenter and co-workers over a number of years and is currently used as the basis of CMU's SMT system. |
| tech,3-2-N03-1012,bq | <term> ontology </term> . We apply our <term> | system | </term> to the task of <term> scoring </term> | #2459 We apply oursystem to the task of scoring alternative speech recognition hypotheses (SRH) in terms of their semantic coherence. |
| tool,15-4-P03-1022,bq | to <term> Byron 's ( 2002 ) manually tuned | system | </term> . <term> Link detection </term> has been | #4040 We evaluate the system on twenty Switchboard dialogues and show that it compares well to Byron's (2002) manually tuned system. |
| other,1-9-C92-3165,bq | with the <term> user </term> . A <term> pilot | system | </term> has shown great effectiveness of | #18261 A pilot system has shown great effectiveness of this approach. |
