Statistical Machine Translation based Passage Retrieval for Cross-Lingual Question Answering — Experiments at NTCIR-6
Tomoyosi Akiba, Kei Shimizu, Atsushi Fujii, Katunobu Itou · NTCIR · 2007
In this paper, we propose a novel approach for Cross-Lingual Question Answering (CLQA), where the statistical machine translation (SMT) is utilized. In the proposed method, the SMT is deeply incorporated into the question answering process, instead of using it as the pre-processing of the mono-lingual QA process as in the previous work. The proposed method can be considered as exploiting the SMT-based passage retrieval for CLQA task. Our experimental results targeting the English-to-Japanese CLQA using the NTCIR CLQA 1 and 2 test collections showed that the proposed method outperformed the previous pretranslation approach.