For many reasons , it is highly desirable to accurately estimate the <term> confidence
confines of <term> syntax </term> , for instance , to the task of <term> semantic interpretation
support linking of <term> lexical entries </term> to their <term> translation equivalents </term>
framework is flexible , allowing fast adaptation to applications and it is scalable . We apply
<term> maximum likelihood method </term> , fail to achieve high <term> performance </term> in
We describe a novel <term> approach </term> to <term> statistical machine translation </term>
best <term> hypothesis </term> corresponding to the <term> LM </term> with the best <term> confidence
quantifiers </term> which are approximations to all and always , e.g. , almost all , almost
tagging </term> , noting that published results to date have not been comparable across <term>
imposed on the available knowledge prior to <term> content determination </term> . We describe
task in building the <term> editor </term> was to define a set of <term> coherence rules </term>
<term> extraction and conversion rules </term> to <term> entries </term> from <term> machine readable
sentence structure </term> , which is vital to <term> machine translation </term> are also
usage and uses these <term> patterns </term> to predict new inputs . <term> Error correction
technology </term> development initiative to advance the state of the art in <term> CSR
laughed is to to laugh , noted I walked : to walk : : I laughed : to laugh ) . But <term>
<term> N-Best sentence hypotheses </term> . To avoid <term> grammar coverage problems </term>
revision support systems </term> to detect and to correct <term> homophone errors </term> . This
are <term> monolingual </term> . We also refer to an <term> evaluation method </term> and plan
computer text generation system </term> designed to create <term> cohesive text </term> through
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