Bilingual chunk alignment in statistical machine translation

In this paper a new algorithm called multilayer filtering (MLF) is proposed for extracting bilingual alignment chunks automatically from a Chinese-English parallel corpus. Multiple layers are used to extract bilingual chunks according to different features of chunks in the bilingual corpus. And the alignment chunks are one-to-one corresponding with each other. The chunking and alignment algorithm doesn´t rely on the information from tagging, parsing, syntax analyzing or segmenting for Chinese corpus as most conventional algorithms do. Preliminary experimental results show that the algorithm achieves a good performance in chunking and alignment. Moreover, the translations generated by this algorithm are much better than the results generated by the baseline (word-based statistical machine translation).