Abstract
Large amounts of bilingual data and monolingual data in the target language are usually used to train statistical machine translation systems. In this paper we propose several semi-supervised techniques within a Bengali English Phrase-based Statistical Machine Translation (SMT) System in order to improve translation quality. We conduct experiments on a Bengali-English dataset and our initial experimental results show improvement in translation quality.
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© 2009 Springer-Verlag Berlin Heidelberg
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Roy, M. (2009). A Semi-supervised Approach to Bengali-English Phrase-Based Statistical Machine Translation. In: Gao, Y., Japkowicz, N. (eds) Advances in Artificial Intelligence. Canadian AI 2009. Lecture Notes in Computer Science(), vol 5549. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01818-3_45
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DOI: https://doi.org/10.1007/978-3-642-01818-3_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01817-6
Online ISBN: 978-3-642-01818-3
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