Meaning preservation in Example-based Machine Translation with structural semantics


Chua, Chong Chai and Lim, Tek Yong and Soon, Lay Ki and Tang, Enya Kong and Ranaivo Malançon, Bali (2017) Meaning preservation in Example-based Machine Translation with structural semantics. Expert Systems with Applications, 78. pp. 242-258. ISSN 0957-4174

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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.

Item Type: Article
Uncontrolled Keywords: Semantics, Example-based Machine Translation, Structured String-Tree Correspondence, Synchronous Structured String-Tree Correspondence, Structural semantics, Semantic roles
Subjects: P Language and Literature > P Philology. Linguistics
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 25 Oct 2020 14:21
Last Modified: 25 Oct 2020 14:21


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