Method for Retrieving a Similar Sentence and Its Application to Machine Translation

In this paper, we propose incorporating similar sentence retrieval in machine translation to improve the translation of hard-to-translate input sentences. If a given input sentence is hard to translate, a sentence similar to the input sentence is retrieved from a monolingual corpus of translatable sentences and then provided to the MT system instead of the original sentence. This method is advantageous in that it relies only on a monolingual corpus. The similarity between an input sentence and each sentence in the corpus is determined from the ratio of the common N-gram. We use two conditions to improve the retrieval precision and add a filtering method to avoid inappropriate sentences. An experiment using a Japanese-to-English MT system in a travel conversation domain proves that our method improves the translation quality of hard-to-translate input sentences by 9.8 %.