A Hierarchical Phrase-Based Model for English-Persian Statistical Machine Translation

Mohaghegh, Mahsa; Sarrafzadeh, Hossein

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Date
2012
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.
Permanent link to Research Bank record:
https://hdl.handle.net/10652/2229
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).
Keywords:
statistical machine translation (SMT), natural language processing, hierarchical phrase-based models
ANZSRC Field of Research:
089999 Information and Computing Sciences not elsewhere classified
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