</term> which can make a fair copy of not only texts but also graphs and tables indispensable
papers in English , many systems to run off texts have been developed . In this paper , we
other,0-1-A94-1026,bq language translation </term> . <term> Japanese texts </term> frequently suffer from the <term>
other,10-5-P82-1035,bq to aid the understanding of <term> scruffy texts </term> has been incorporated into a working
other,12-3-C92-4207,bq </term> , which takes <term> natural language texts </term> and produces a <term> model </term>
other,2-1-C94-1026,bq errors </term> . To align <term> bilingual texts </term> becomes a crucial issue recently
other,24-1-A92-1027,bq specific information from <term> unrestricted texts </term> where many of the <term> words </term>
other,24-4-I05-2014,bq systems </term> outputting <term> unsegmented texts </term> with , for instance , <term> statistical
other,25-5-P82-1035,bq </term> , which understands <term> scruffy texts </term> in the domain of Navy messages .
other,26-2-P82-1035,bq that differ significantly from <term> neat texts </term> , posing special problems for readers
other,27-1-P82-1035,bq newspaper stories </term> and other <term> edited texts </term> . However , a great deal of <term>
other,3-3-C94-1026,bq proposed . We postulate that <term> source texts </term> and <term> target texts </term> should
other,6-2-C88-1044,bq </term> . We examine a broad range of <term> texts </term> to show how the distribution of <term>
other,6-2-P82-1035,bq , a great deal of <term> natural language texts </term> e.g. , <term> memos </term> , rough <term>
other,6-3-C94-1026,bq <term> source texts </term> and <term> target texts </term> should share the same concepts ,
other,7-6-C94-1026,bq experimental objects are <term> Chinese-English texts </term> , which are selected from different
other,8-3-C86-1132,bq synthesize <term> bilingual or multMingual texts </term> . A method for <term> error correction
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