Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Data Augmentation and Terminology Integration for Domain-Specific
  Sinhala-English-Tamil Statistical Machine Translation   Out of vocabulary (OOV) is a problem in the context of Machine Translation
(MT) in low-resourced languages. When source and/or target languages are
morphologically rich, it becomes even worse. Bilingual list integration is an
approach to address the OOV problem. This allows more words to be translated
than are in the training data. However, since bilingual lists contain words in
the base form, it will not translate inflected forms for morphologically rich
languages such as Sinhala and Tamil. This paper focuses on data augmentation
techniques where bilingual lexicon terms are expanded based on case-markers
with the objective of generating new words, to be used in Statistical machine
Translation (SMT). This data augmentation technique for dictionary terms shows
improved BLEU scores for Sinhala-English SMT.

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The categories of this paper are: q-fin
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The categories of this paper are: comp-gas
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The categories of this paper are: nucl-ex
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The categories of this paper are: bayes-an
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The categories of this paper are: patt-sol
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The categories of this paper are: quant-ph
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The categories of this paper are: q-bio
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The categories of this paper are: supr-con
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The categories of this paper are: econ
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The categories of this paper are: eess
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The categories of this paper are: chao-dyn
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-th
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The categories of this paper are: mtrl-th
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The categories of this paper are: acc-phys
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The categories of this paper are: q-alg