</term> . At MIT Lincoln Laboratory , we have been developing a <term> Korean-to-English machine
automated acquisition of grammars </term> . Having been trained on <term> Korean newspaper articles
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
</term> of <term> SMT models </term> has never been evaluated and compared with that of the
last few years dramatic improvements have been made , and a number of comparative evaluations
translation system </term> . <term> STTK </term> has been developed by the presenter and co-workers
system </term> . It has also successfully been coupled with <term> rule-based and example
Translation ( SMT ) </term> but which have not been addressed satisfactorily by the <term> SMT
variety of <term> SMT algorithms </term> have been built and empirically tested whereas little
</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
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