Translation of Untranslatable Words - Integration of Lexical Approximation and Phrase-Table Extension Techniques into Statistical Machine Translation

摘要

This paper proposes a method for handling out-of-vocabulary (OOV) words that eannot be translated using eonventional phrase-based statistieal machine translation (SMT) systems. For a given OOV word, lexical approximation techniques are utilized to identify spellirg and inflectional werd variants that occur in the training data. All OOV words in the soures sentence are then replaced with appropriate word variants found in the training corpus, thus reducing the number of OOV words in the input. Moreover, in order to increase the coverage of such word translations, the SMT translation model is extended by adding new phrase translations for all source language words that do not have a single-word entry in the original phrase-table but only appear in the context of larger phrases. The effectiveness of the proposed methods is investigated for the translation of Hindi to English. Chinese, and Japanese.