Automatic creation of a word aligned Sinhala-Tamil parallel corpus

Abstract

A parallel corpus aligned at both sentence and word level is an important prerequisite in statistical machine translation. However, manual creation of such a parallel corpus is time consuming, and requires experts fluent in both languages. This paper presents the first ever empirical evaluation carried out to identify the best unsupervised word alignment technique for Sinhala and Tamil. It also presents a novel approach that combines the output of individual aligners, which outperforms the solitary use of these aligners. Sentence aligned parallel text from annual reports and letters of Sri Lankan Government institutions, and order papers from the Parliament of Sri Lanka were used in the evaluation.