Generating Term Transliterations Using Contextual Information and Validating Generated Results Using Web Corpora

Abstract

Transliterating foreign entities into Chinese is usually done through direct-style approach. The direct-style approach transliterates each syllable rendered from foreign terms into Chinese directly. Not every syllable can be rendered. An approach utilizing contextual information for term transliteration is proposed in this paper to attack this problem. Traditionally, evaluating transliteration performances always uses character and word error rates. However, many transliteration variants of the same term always found. Validating the generated results using Web corpora is more suitable and is proposed in this paper. Using the proposed evaluation method, experiments on term transliteration were conducted. From the experimental results show that taking contextual information is helpful to term transliteration and validating the generated results using Web corpora can provide more concrete evidences to transliteration evaluation.