</term> . At MIT Lincoln Laboratory , we have been developing a <term> Korean-to-English machine
system response </term> to <term> users </term> has been extensively studied by the <term> natural
</term> , where each <term> word string </term> has been obtained by using a different <term> LM </term>
natural language generator </term> have recently been proposed , but a fundamental concern is
system </term> . <term> Link detection </term> has been regarded as a core technology for the <term>
city bus information system </term> that has been developed at our laboratory . Experimental
that published results to date have not been comparable across <term> corpora </term> or
approach to <term> summarization </term> has been shown to work in <term> documents </term> of
translation models </term> that have recently been adopted in the literature on <term> machine
lexical sample task </term> . Much effort has been put in designing and evaluating dedicated
last few years dramatic improvements have been made , and a number of comparative evaluations
Translation ( SMT ) </term> but which have not been addressed satisfactorily by the <term> SMT
</term> with <term> human judgment </term> has been investigated systematically on two different
ways . We first apply approaches that have been proposed for <term> predicting top-level
of its usefulness and usability , it has been used successfully in a research context
English , many systems to run off texts have been developed . In this paper , we report a
be successfully obtained . An attempt has been made to use an <term> Augmented Transition
<term> Chat-80 </term> . <term> Chat-80 </term> has been designed to be both efficient and easily
<term> text-understanding systems </term> have been designed under the assumption that the
<term> utterance </term> , but they have often been disregarded , perhaps because it seemed
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