Yong-jun Han


2021

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Translation Memory Retrieval Using Lucene
Kwang-hyok Kim | Myong-ho Cho | Chol-ho Ryang | Ju-song Im | Song-yong Cho | Yong-jun Han
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)

Translation Memory (TM) system, a major component of computer-assisted translation (CAT), is widely used to improve human translators’ productivity by making effective use of previously translated resource. We propose a method to achieve high-speed retrieval from a large translation memory by means of similarity evaluation based on vector model, and present the experimental result. Through our experiment using Lucene, an open source information retrieval search engine, we conclude that it is possible to achieve real-time retrieval speed of about tens of microseconds even for a large translation memory with 5 million segment pairs.