A Hierarchical Phrase-Based Model for English-Persian Statistical Machine Translation
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Authors
Mohaghegh, Mahsa
Sarrafzadeh, Hossein
Sarrafzadeh, Hossein
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Date
2012
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Conference Contribution - Paper in Published Proceedings
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Keyword
statistical machine translation (SMT)
natural language generation (computer science)
hierarchical phrase-based models
natural language generation (computer science)
hierarchical phrase-based models
ANZSRC Field of Research Code (2020)
Citation
Mohaghegh, M., and Sarrafzadeh, H. (2012). A Hierarchical Phrase-Based Model for English-Persian Statistical Machine Translation. Innovations 12, 8th International Conference on Innovations in Information Technology. 18-20 March. pp. 205-208. doi: 10.1109/INNOVATIONS.2012.6207733.
Abstract
In this paper we show that a hierarchical phrasebased translation system will outperform a classical (nonhierarchical) phrase-based system in the English-to-Persian translation direction, yet for the Persian-to-English direction, the classical phrase-based system is preferable. We seek to explain why this is so, and detail a series of translation experiments with our SMT system using various bilingual corpora each with both toolkits Moses (non-hierarchical) and Joshua (hierarchical).
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10.1109/INNOVATIONS.2012.6207733
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