TRANSDUCER FOR AUTO-CONVERT OF ARCHAIC TO PRESENT DAY ENGLISH FOR MACHINE READABLE TEXT: A SUPPORT FOR COMPUTER ASSISTED LANGUAGE LEARNING

Abstract

There exist some English literary works where some archaic words are still used; they are relatively distinct from Present Day English (PDE). We might observe some archaic words that have undergone regular changing patterns: for instances, archaic modal verbs like mightst, darest, wouldst. The –st ending historically disappears, resulting on might, dare and would. (wouldst > would). However, some archaic words undergo distinct processes, resulting on unpredictable pattern; The occurrence frequency for archaic english pronouns like thee ‘you’, thy ‘your’, thyself ‘yourself’ are quite high. Students that are Non-Native speakers of English might come across many difficulties when they encounter English texts which include these kinds of archaic words. How might computer be a help for the student? This paper aims on providing some supports from the perspective of Computer Assisted Language Learning (CALL). It proposes some designs of lexicon transducers by using Local Grammar Graphs (LGG) for auto-convert of the archaic words to PDE in a literature machine readable text. The transducer is applied to a machine readable text that is taken from Sir Walter Scott’s Ivanhoe. The archaic words in the corpus can be converted automatically to PDE. The transducer also allows the presentation of the two forms (Arhaic and PDE), the PDE lexicons-only, or the original (Archaic Lexicons) form-only. This will help students in understanding English literature works better. All the linguistic resources here are machine readable, ready to use, maintainable and open for further development. The method might be adopted for lexicon tranducer for another language too.