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Identification of Bilingual Segments for Translation Generation

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 8819)

Abstract

We present an approach that uses known translation forms in a validated bilingual lexicon and identifies bilingual stem and suffix segments. By applying the longest sequence common to pair of orthographically similar translations we initially induce the bilingual suffix transformations (replacement rules). Redundant analyses are discarded by examining the distribution of stem pairs and associated transformations. Set of bilingual suffixes conflating various translation forms are grouped. Stem pairs sharing similar transformations are subsequently clustered which serves as a basis for the generative approach. The primary motivation behind this work is to eventually improve the lexicon coverage by utilising the correct bilingual entries in suggesting translations for OOV words. In the preliminary results, we report generation results, wherein, 90% of the generated translations are correct. This was achieved when both the bilingual segments (bilingual stem and bilingual suffix) in the bilingual pair being analysed are known to have occurred in the training data set.

Keywords

  • Translation lexicon coverage
  • Cluster analysis
  • Bilingual morphology
  • Translation generation

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Karimbi Mahesh, K., Gomes, L., Lopes, J.G.P. (2014). Identification of Bilingual Segments for Translation Generation. In: Blockeel, H., van Leeuwen, M., Vinciotti, V. (eds) Advances in Intelligent Data Analysis XIII. IDA 2014. Lecture Notes in Computer Science, vol 8819. Springer, Cham. https://doi.org/10.1007/978-3-319-12571-8_15

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  • DOI: https://doi.org/10.1007/978-3-319-12571-8_15

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12570-1

  • Online ISBN: 978-3-319-12571-8

  • eBook Packages: Computer ScienceComputer Science (R0)