A New Diagnostic System for J-E translation ILTS

A new diagnostic system has been devel-oped for an interactive template-structured intelligent language tutoring system (ILTS) for Japanese-English translation where an efficient heaviest common sequence (HCS) matching algorithm and a ‘part-of-speech tagged (POST) parser ’ play a key role. This is implemented by exploiting the system template which consists of a complex tran-sition networks comprising both model (cor-rect) translations and many typical erro-neous translations characteristic of nonna-tive beginners all collected and extracted from translations of about 200 monitors. By selecting, from among many candidates’ paths in the system template, a path hav-ing a HCS with the student’s input trans-lation as a best matched sentence, the tem-plate structure of the diagnostic system al-lows the potentially complicated bug find-ing processes in natural language to be im-plemented by a much simpler and efficient HCS string matching algorithm [20]. To improve the precision of a parser, we have developed a ‘probabilistic POST parser’ where we have eliminated ambiguity in part-of-speeches by manually pre-assigning POS tags to all words in potentially correct paths of the template. Combining the template-based diagnostic system and the parser, we found that the ILTS is capable of providing most adequate diagnostic messages and a tutoring strategy with appropriate com-ments after analyzing the keyed-in trans-lated sentences from students.