</term> can be obtained . To support engaging human users in robust , <term> mixed-initiative
other,22-1-H01-1042,bq devised for the <term> evaluation </term> of <term> human language learners </term> , to the <term> output
other,12-2-H01-1042,bq provide information about both the <term> human language learning process </term> , the <term>
other,5-8-H01-1042,bq </term> . Some of the extracts were <term> expert human translations </term> , others were <term> machine
other,19-9-H01-1042,bq believed the sample output to be an <term> expert human translation </term> or a <term> machine translation
tech,9-1-H01-1049,bq LCS ) </term> is a new paradigm for <term> human interaction with data sources </term> . We
other,27-2-N01-1003,bq of <term> feedback </term> provided by <term> human judges </term> . We reconceptualize the task
other,17-2-P01-1056,bq system </term> by eliciting <term> subjective human judgments </term> . In order to perform an
other,8-3-N03-1012,bq annotation experiment </term> and showed that <term> human annotators </term> can reliably differentiate
tech,27-2-N03-4004,bq <term> languages </term> by leveraging <term> human language technology </term> . The <term> JAVELIN
lr,26-6-P03-1050,bq </term> , <term> affix lists </term> , and <term> human annotated text </term> , in addition to an
other,30-2-C04-1036,bq application </term> ) at a good level of <term> human agreement </term> . Motivated by this semantic
other,13-4-C04-1096,bq </term> that are naturally recognized by <term> humans </term> . We conducted <term> psychological
measure(ment),7-5-H05-1012,bq algorithm </term> is contrasted with <term> human annotation performance </term> . This paper
other,7-6-E06-1031,bq of the new <term> measure </term> with <term> human judgment </term> has been investigated systematically
other,20-8-E06-1031,bq automatic evaluation measures </term> and <term> human judgment </term> . In this paper , we investigate
other,14-4-E06-1035,bq <term> ASR output </term> as opposed to <term> human transcription </term> . Examination of the
other,7-1-T78-1028,bq <term> computational theory </term> of <term> human plausible reasoning </term> constructed from
other,9-1-P80-1004,bq integral and inescapable process in <term> human understanding of natural language </term>
view , but claims that direct imitation of human performance is not the best way to implement
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