Automatic Korean Phoneme Generation Via Input-Text Preprocessing and Disambiguation

Abstract

This paper proposes an Automatic Korean Phoneme Generator (AKPG) that can be adapted to various natural language processing systems that handle raw input-text from users such as the Korean pronunciation education system. Resolving noise and ambiguity is a precondition for correct natural language processing. In order to satisfy this condition, the AKPG, as a module of an NLP system, combines linguistic and IR methods. Preprocessing modules are incorporated into the AKPG to handle spelling-errors that render correct phoneme generation impossible. In addition, the preprocessing modules convert alphanumeric symbols into Korean characters. Finally, in order to remove part-of-speech (POS) ambiguities and those of homographs with the same POS, homograph collocations are collected from a large corpus using the IR method. In addition, those homographs are integrated into dependency rules for partial parsing.