Concordance

Query N04-1022 18 >
Random sample 18 (839.2 per million)

tech,2-1-N04-1022,bq	We present <term> Minimum Bayes-Risk ( MBR ) decoding </term> for <term> statistical machine translation </term> .	#6545 We presentMinimum Bayes-Risk ( MBR ) decoding for statistical machine translation.
tech,9-1-N04-1022,bq	We present <term> Minimum Bayes-Risk ( MBR ) decoding </term> for <term> statistical machine translation </term> .	#6552 We present Minimum Bayes-Risk (MBR) decoding forstatistical machine translation.
other,6-2-N04-1022,bq	This statistical approach aims to minimize <term> expected loss of translation errors </term> under <term> loss functions </term> that measure <term> translation performance </term> .	#6562 This statistical approach aims to minimizeexpected loss of translation errors under loss functions that measure translation performance.
other,12-2-N04-1022,bq	This statistical approach aims to minimize <term> expected loss of translation errors </term> under <term> loss functions </term> that measure <term> translation performance </term> .	#6568 This statistical approach aims to minimize expected loss of translation errors underloss functions that measure translation performance.
measure(ment),16-2-N04-1022,bq	This statistical approach aims to minimize <term> expected loss of translation errors </term> under <term> loss functions </term> that measure <term> translation performance </term> .	#6572 This statistical approach aims to minimize expected loss of translation errors under loss functions that measuretranslation performance.
other,5-3-N04-1022,bq	We describe a hierarchy of <term> loss functions </term> that incorporate different levels of <term> linguistic information </term> from <term> word strings </term> , <term> word-to-word alignments </term> from an <term> MT system </term> , and <term> syntactic structure </term> from <term> parse-trees </term> of <term> source and target language sentences </term> .	#6580 We describe a hierarchy ofloss functions that incorporate different levels of linguistic information from word strings, word-to-word alignments from an MT system, and syntactic structure from parse-trees of source and target language sentences.
other,12-3-N04-1022,bq	We describe a hierarchy of <term> loss functions </term> that incorporate different levels of <term> linguistic information </term> from <term> word strings </term> , <term> word-to-word alignments </term> from an <term> MT system </term> , and <term> syntactic structure </term> from <term> parse-trees </term> of <term> source and target language sentences </term> .	#6587 We describe a hierarchy of loss functions that incorporate different levels oflinguistic information from word strings, word-to-word alignments from an MT system, and syntactic structure from parse-trees of source and target language sentences.
other,15-3-N04-1022,bq	We describe a hierarchy of <term> loss functions </term> that incorporate different levels of <term> linguistic information </term> from <term> word strings </term> , <term> word-to-word alignments </term> from an <term> MT system </term> , and <term> syntactic structure </term> from <term> parse-trees </term> of <term> source and target language sentences </term> .	#6590 We describe a hierarchy of loss functions that incorporate different levels of linguistic information fromword strings, word-to-word alignments from an MT system, and syntactic structure from parse-trees of source and target language sentences.
other,18-3-N04-1022,bq	We describe a hierarchy of <term> loss functions </term> that incorporate different levels of <term> linguistic information </term> from <term> word strings </term> , <term> word-to-word alignments </term> from an <term> MT system </term> , and <term> syntactic structure </term> from <term> parse-trees </term> of <term> source and target language sentences </term> .	#6593 We describe a hierarchy of loss functions that incorporate different levels of linguistic information from word strings,word-to-word alignments from an MT system, and syntactic structure from parse-trees of source and target language sentences.
tech,22-3-N04-1022,bq	We describe a hierarchy of <term> loss functions </term> that incorporate different levels of <term> linguistic information </term> from <term> word strings </term> , <term> word-to-word alignments </term> from an <term> MT system </term> , and <term> syntactic structure </term> from <term> parse-trees </term> of <term> source and target language sentences </term> .	#6597 We describe a hierarchy of loss functions that incorporate different levels of linguistic information from word strings, word-to-word alignments from anMT system, and syntactic structure from parse-trees of source and target language sentences.
other,26-3-N04-1022,bq	We describe a hierarchy of <term> loss functions </term> that incorporate different levels of <term> linguistic information </term> from <term> word strings </term> , <term> word-to-word alignments </term> from an <term> MT system </term> , and <term> syntactic structure </term> from <term> parse-trees </term> of <term> source and target language sentences </term> .	#6601 We describe a hierarchy of loss functions that incorporate different levels of linguistic information from word strings, word-to-word alignments from an MT system, andsyntactic structure from parse-trees of source and target language sentences.
other,29-3-N04-1022,bq	We describe a hierarchy of <term> loss functions </term> that incorporate different levels of <term> linguistic information </term> from <term> word strings </term> , <term> word-to-word alignments </term> from an <term> MT system </term> , and <term> syntactic structure </term> from <term> parse-trees </term> of <term> source and target language sentences </term> .	#6604 We describe a hierarchy of loss functions that incorporate different levels of linguistic information from word strings, word-to-word alignments from an MT system, and syntactic structure fromparse-trees of source and target language sentences.
other,31-3-N04-1022,bq	We describe a hierarchy of <term> loss functions </term> that incorporate different levels of <term> linguistic information </term> from <term> word strings </term> , <term> word-to-word alignments </term> from an <term> MT system </term> , and <term> syntactic structure </term> from <term> parse-trees </term> of <term> source and target language sentences </term> .	#6606 We describe a hierarchy of loss functions that incorporate different levels of linguistic information from word strings, word-to-word alignments from an MT system, and syntactic structure from parse-trees ofsource and target language sentences.
tech,6-4-N04-1022,bq	We report the performance of the <term> MBR decoders </term> on a <term> Chinese-to-English translation task </term> .	#6618 We report the performance of theMBR decoders on a Chinese-to-English translation task.
other,10-4-N04-1022,bq	We report the performance of the <term> MBR decoders </term> on a <term> Chinese-to-English translation task </term> .	#6622 We report the performance of the MBR decoders on aChinese-to-English translation task.
tech,4-5-N04-1022,bq	Our results show that <term> MBR decoding </term> can be used to tune <term> statistical MT </term> performance for specific <term> loss functions </term> .	#6630 Our results show thatMBR decoding can be used to tune statistical MT performance for specific loss functions.
tech,11-5-N04-1022,bq	Our results show that <term> MBR decoding </term> can be used to tune <term> statistical MT </term> performance for specific <term> loss functions </term> .	#6637 Our results show that MBR decoding can be used to tunestatistical MT performance for specific loss functions.
other,16-5-N04-1022,bq	Our results show that <term> MBR decoding </term> can be used to tune <term> statistical MT </term> performance for specific <term> loss functions </term> .	#6642 Our results show that MBR decoding can be used to tune statistical MT performance for specificloss functions.


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