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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.