article considers approaches which rerank the output of an existing <term> probabilistic parser
tech,3-7-P05-1067,bq <term> model </term> . We evaluate the <term> outputs </term> of our <term> MT system </term> using
other,12-4-P05-2016,bq </term> and plan to compare our <term> system 's output </term> with a <term> benchmark system </term>
other,9-4-E06-1035,bq <term> performance </term> of using <term> ASR output </term> as opposed to <term> human transcription
other,9-6-E06-1035,bq transcription errors </term> inevitable in <term> ASR output </term> have a negative impact on models
other,18-1-P06-4014,bq pipeline </term> that capitalizes on <term> output quality </term> . The demonstrator embodies
</term> of a <term> parser </term> 's multiple output . Some examples of <term> paraphrasing </term>
by gathering <term> statistics </term> on the output of other <term> linguistic tools </term> .
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