A Hybrid Model for Extracting Transliteration Equivalents

Abstract

Several models for transliteration pair acquisition have been proposed to overcome the out-of-vocabulary problem caused by transliterations. To date, however, there has been little literature regarding a framework that can accommodate several models at the same time. Moreover, there is little concern for validating acquired transliteration pairs using up-to-date corpora, such as web documents. To address these problems, we propose a hybrid model for transliteration pair acquisition. In this paper, we concentrate on a framework for combining several models for transliteration pair acquisition. Experiments showed that our hybrid model was more effective than each individual transliteration pair acquisition model alone.