other,27-3-H01-1041,bq case markers </term> , relatively <term> free word order </term> , and frequent omissions of
tech,7-4-H01-1041,bq quality <term> translation </term> via <term> word sense disambiguation </term> and accurate
tech,12-4-H01-1041,bq disambiguation </term> and accurate <term> word order generation </term> of the <term> target
other,18-4-H01-1042,bq language essays </term> in less than 100 <term> words </term> . Even more illuminating was the
other,8-10-H01-1042,bq Additionally , they were asked to mark the <term> word </term> at which they made this decision
other,4-3-H01-1058,bq <term> oracle </term> knows the <term> reference word string </term> and selects the <term> word
other,10-3-H01-1058,bq word string </term> and selects the <term> word string </term> with the best <term> performance
measure(ment),19-3-H01-1058,bq <term> performance </term> ( typically , <term> word or semantic error rate </term> ) from a list
other,29-3-H01-1058,bq error rate </term> ) from a list of <term> word strings </term> , where each <term> word string
other,34-3-H01-1058,bq <term> word strings </term> , where each <term> word string </term> has been obtained by using
model,24-3-P01-1004,bq </term> superior to any of the tested <term> word N-gram models </term> . Further , in their
other,3-3-P01-1008,bq approach yields <term> phrasal and single word lexical paraphrases </term> as well as <term>
other,11-1-P01-1009,bq analysis </term> for a large class of <term> words </term> called <term> alternative markers </term>
other,1-2-P01-1009,bq </term> , and <term> besides </term> . These <term> words </term> appear frequently enough in <term>
other,7-4-N03-1017,bq <term> phrases </term> longer than three <term> words </term> and learning <term> phrases </term> from
measure(ment),20-3-N03-1018,bq significantly reduce <term> character and word error rate </term> , and provide evaluation
tech,40-1-N03-1033,bq jointly conditioning on multiple consecutive words </term> , ( iii ) effective use of <term> priors
other,66-1-N03-1033,bq ) fine-grained modeling of <term> unknown word features </term> . Using these ideas together
tech,6-1-N03-2017,bq <term> syntax-based constraint </term> for <term> word alignment </term> , known as the <term> cohesion
model,14-4-N03-2036,bq projections </term> using an underlying <term> word alignment </term> . We show experimental
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