this approach is that knowledge concerning translation equivalence of expressions may be directly
lr,12-2-P01-1008,bq </term> from a <term> corpus of multiple English translations </term> of the same <term> source text </term>
lr,34-3-N03-1018,bq <term> automatic extraction </term> of <term> translation lexicons </term> from <term> printed text </term>
lr,9-1-H05-2007,bq systematic <term> patterns </term> in <term> translation data </term> using <term> part-of-speech tag
measure(ment),15-4-H05-1012,bq well as improvement on several <term> machine translation tests </term> . <term> Performance </term> of
measure(ment),16-2-N04-1022,bq <term> loss functions </term> that measure <term> translation performance </term> . We describe a hierarchy
measure(ment),17-8-P05-1067,bq the <term> IBM models </term> in both <term> translation speed and quality </term> . In this paper
measure(ment),20-1-I05-5008,bq reference sets </term> in objective <term> machine translation evaluation measures </term> like <term> BLEU
measure(ment),20-3-P05-1032,bq orders of magnitude with no loss in <term> translation quality </term> . We describe a novel <term>
measure(ment),23-3-H05-1095,bq </term> based on the maximization of <term> translation accuracy </term> , as measured with the <term>
measure(ment),3-1-I05-5003,bq <term> Web </term> . The task of <term> machine translation ( MT ) evaluation </term> is closely related
measure(ment),31-3-P05-1048,bq does not yield significantly better <term> translation quality </term> than the <term> statistical
model,21-1-N03-1017,bq , previously proposed <term> phrase-based translation models </term> . Within our framework , we
model,4-1-N03-1017,bq % ) . We propose a new <term> phrase-based translation model </term> and <term> decoding algorithm
model,8-1-H05-1101,bq </term> associated with <term> probabilistic translation models </term> that have recently been adopted
other,0-2-A94-1017,bq translation </term> . <term> Spoken language translation </term> requires ( 1 ) an accurate <term> translation
other,0-4-H05-1095,bq <term> NIST evaluation metric </term> . <term> Translations </term> are produced by means of a <term> beam-search
other,1-2-N03-2036,bq phrase-based models </term> . The <term> units of translation </term> are <term> blocks </term> - pairs of <term>
other,10-3-P05-1048,bq disambiguation model </term> to choose <term> translation candidates </term> for a typical <term> IBM
other,10-4-N04-1022,bq decoders </term> on a <term> Chinese-to-English translation task </term> . Our results show that <term>
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