other,16-3-H01-1042,bq the <term> intelligibility </term> of <term> MT output </term> . A <term> language learning experiment
other,11-3-I05-6011,bq </term> and improving <term> machine translation outputs </term> . Annotating <term> honorifics </term>
other,30-2-H05-2007,bq patterns </term> in <term> machine translation output </term> . Automatic <term> evaluation metrics
other,16-6-H01-1042,bq experiment using <term> machine translation output </term> . Subjects were given a set of up
other,11-8-H01-1042,bq </term> , others were <term> machine translation outputs </term> . The subjects were given three minutes
other,38-4-I05-2014,bq </term> which usually segment their <term> outputs </term> . We present the first known <term>
other,9-4-E06-1035,bq <term> performance </term> of using <term> ASR output </term> as opposed to <term> human transcription
the <term> shared derivation forest </term> output by a prior <term> RCL parser </term> for a
other,15-5-N03-1026,bq <term> grammaticality </term> of the <term> system output </term> due to the use of a <term> constraint-based
. In this paper we show how two standard outputs from <term> information extraction ( IE )
other,9-6-E06-1035,bq transcription errors </term> inevitable in <term> ASR output </term> have a negative impact on models
measure(ment),6-3-H05-1117,bq <term> methods </term> for <term> scoring system output </term> is an impediment to progress in the
article considers approaches which rerank the output of an existing <term> probabilistic parser
other,38-1-N03-1018,bq through its transformation into the <term> noisy output </term> of an <term> OCR system </term> . The
other,16-2-N03-1018,bq on <term> post-processing </term> the <term> output </term> of black-box <term> OCR systems </term>
other,28-1-H01-1042,bq human language learners </term> , to the <term> output </term> of <term> machine translation ( MT
by gathering <term> statistics </term> on the output of other <term> linguistic tools </term> .
tech,3-7-P05-1067,bq <term> model </term> . We evaluate the <term> outputs </term> of our <term> MT system </term> using
other,21-3-N03-1001,bq particular <term> domain </term> ; the <term> output </term> of <term> recognition </term> with this
other,18-1-P06-4014,bq pipeline </term> that capitalizes on <term> output quality </term> . The demonstrator embodies
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