| other,11-1-P05-1034,ak | We describe a novel approach to <term> statistical machine translation </term> that combines <term> syntactic information </term> in the <term> source language </term> with recent advances in <term> phrasal translation </term> . | #8850 We describe a novel approach to statistical machine translation that combines syntactic information in the source language with recent advances in phrasal translation. | |
| tech,21-1-P05-1034,ak | We describe a novel approach to <term> statistical machine translation </term> that combines <term> syntactic information </term> in the <term> source language </term> with recent advances in <term> phrasal translation </term> . | #8860 We describe a novel approach to statistical machine translation that combines syntactic information in the source language with recent advances in phrasal translation . | |
| lr,3-3-P05-1034,ak | We align a <term> parallel corpus </term> , project the <term> source dependency parse </term> onto the <term> target sentence </term> , extract <term> dependency treelet translation pairs </term> , and train a <term> tree-based ordering model </term> . | #8885 We align a parallel corpus , project the source dependency parse onto the target sentence, extract dependency treelet translation pairs, and train a tree-based ordering model. | |
| tech,27-4-P05-1034,ak | We describe an efficient <term> decoder </term> and show that using these <term> tree-based models </term> in combination with conventional <term> SMT models </term> provides a promising approach that incorporates the power of <term> phrasal SMT </term> with the linguistic generality available in a <term> parser </term> . | #8938 We describe an efficient decoder and show that using these tree-based models in combination with conventional SMT models provides a promising approach that incorporates the power of phrasal SMT with the linguistic generality available in a parser. |
