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Expert Systems with ApplicationsVolume 78, 15 July 2017, Pages 242-258

Meaning preservation in Example-based Machine Translation with structural semantics(Article)

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  • aFaculty of Computing and Informatics, Multimedia University, Persiaran Multimedia, 63100 Cyberjaya, Selangor, Malaysia
  • bUniversiti Sains Malaysia, Gelugor, 11800, Pulau, Pinang, Malaysia
  • cFaculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Sarawak, Malaysia

Abstract

The main tasks in Example-based Machine Translation (EBMT) comprise of source text decomposition, following with translation examples matching and selection, and finally adaptation and recombination of the target translation. As the natural language is ambiguous in nature, the preservation of source text's meaning throughout these processes is complex and challenging. A structural semantics is introduced, as an attempt towards meaning-based approach to improve the EBMT system. The structural semantics is used to support deeper semantic similarity measurement and impose structural constraints in translation examples selection. A semantic compositional structure is derived from the structural semantics of the selected translation examples. This semantic compositional structure serves as a representation structure to preserve the consistency and integrity of the input sentence's meaning structure throughout the recombination process. In this paper, an English to Malay EBMT system is presented to demonstrate the practical application of this structural semantics. Evaluation of the translation test results shows that the new translation framework based on the structural semantics has outperformed the previous EBMT framework. © 2017 Elsevier Ltd

SciVal Topic Prominence

Topic: Statistical Machine Translation | Translation Memory | Parallel Corpora
Prominence percentile: 92.375
 

Author keywords

Example-based Machine TranslationSemantic rolesStructural semanticsStructured String-Tree CorrespondenceSynchronous Structured String-Tree Correspondence

Indexed keywords

Engineering controlled terms:Computational linguisticsComputer aided language translationForestryNatural language processing systemsText processing
Engineering uncontrolled termsExample based machine translationsSemantic rolesStructural semanticsStructured String-Tree CorrespondenceSynchronous Structured String-Tree Correspondence
Engineering main heading:Semantics
  • ISSN: 09574174
  • CODEN: ESAPE
  • Source Type: Journal
  • Original language: English
  • DOI: 10.1016/j.eswa.2017.02.021
  • Document Type: Article
  • Publisher: Elsevier Ltd

  Chua, C.C.; Faculty of Computing and Informatics, Multimedia University, Persiaran Multimedia, 63100 Cyberjaya, Selangor, Malaysia;
© Copyright 2017 Elsevier B.V., All rights reserved.

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