| by <term> extrapolation </term> . Thus , our | model | , <term> TDMT on APs </term> , meets the vital | #20351 Thus, our model, TDMT on APs, meets the vital requirements of spoken language translation. | |
| other,40-2-C94-1030,bq | methods using <term> m-th order Markov chain | model | </term> for <term> Japanese kanji-kana characters | #20685 In order to judge three types of the errors, which are characters wrongly substituted, deleted or inserted in a Japanese bunsetsu and an English word, and to correct these errors, this paper proposes new methods using m-th order Markov chain model for Japanese kanji-kana characters and English alphabets, assuming that Markov probability of a correct chain of syllables or kanji-kana characters is greater than that of erroneous chains. |
| model,1-1-C94-1061,bq | </term> and <term> Spanish </term> . A <term> grammar | model | </term> for <term> concurrent , object-oriented | #20815 A grammar model for concurrent, object-oriented natural language parsing is introduced. |
| tech,2-3-C94-1061,bq | The underlying <term> concurrent computation | model | </term> relies upon the <term> actor paradigm | #20858 The underlying concurrent computation model relies upon the actor paradigm. |
| model,5-1-C94-1080,bq | </term> of an <term> object-oriented grammar | model | </term> is considered . The model is based | #21007 The behavioral specification of an object-oriented grammar model is considered. |
| grammar model </term> is considered . The | model | is based on full <term> lexicalization </term> | #21012 The model is based on full lexicalization, head-orientation via valency constraints and dependency relations, inheritance as a means for non-redundant lexicon specification, and concurrency of computation. | |
| model,1-3-C94-1080,bq | computation </term> . The <term> computation | model | </term> relies upon the <term> actor paradigm | #21043 The computation model relies upon the actor paradigm, with concurrency entering through asynchronous message passing between actors. |
| model,6-1-H94-1014,bq | introduces a simple mixture <term> language | model | </term> that attempts to capture <term> long | #21218 This paper introduces a simple mixture language model that attempts to capture long distance constraints in a sentence or paragraph. |
| model,1-2-H94-1014,bq | </term> or <term> paragraph </term> . The <term> | model | </term> is an <term> m-component mixture </term> | #21233 Themodel is an m-component mixture of trigram models. |
| model,25-4-H94-1014,bq | </term> as compared to using a <term> trigram | model | </term> . This paper describes a method of | #21289 Using the BU recognition system, experiments show a 7% improvement in recognition accuracy with the mixture trigram models as compared to using a trigram model. |
