Phrase-Level Grouping for Lexical Gap Resolution in Korean-Vietnamese SMT

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 781)

Abstract

A lexical gap easily leads to word alignment errors, which impairs a translation quality. This paper proposes some simple ideas to resolve the difficulty of handling the lexical gap. In morphologically rich languages, a predicate has a complex structure consisting of many morphemes, so we mainly address the issue of how to group the component morphemes by employing morpho-syntactic filters and statistical information from the SMT phrase table. In addition, we abstract grouping results depending on a lexical choice of the target side to enhance translation probabilities. In the experiment, we not only investigate how each method has an effect on Korean-to-Vietnamese SMT, but also show a promising improvement of BLEU score.

Keywords

Statistical machine translation Lexical gap resolution Morpheme group Multi-word expression Korean-Vietnamese translation 

Notes

Acknowledgment

This work was partly supported by the ICT R&D program of MSIP/IITP [R7119-16-1001, Core technology development of the real-time simultaneous speech translation based on knowledge enhancement], the ICT Consilience Creative Program of MSIP/IITP [R0346-16-1007] and SYSTRAN.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringPohang University of Science and TechnologyPohangRepublic of Korea

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