Unlike most Western languages, there are no typographic boundaries between words in written Japanese and Chinese. Word segmentation is thus normally adopted as an initial step in most natural language processing tasks for these Asian languages. Although word segmentation techniques have improved greatly both theoretically and practically, there still remains some problems to be tackled. In this paper, we present an effective approach in extracting Chinese and Japanese phrases without conducting word segmentation beforehand, using a sampling-based multilingual alignment method. According to our experiments, it is also feasible to train a statistical machine translation system on a small Japanese-Chinese training corpus without performing word segmentation beforehand.