A Multilayered Bilingual Word-Alignment Algorithm

Bilingual word alignment is to find the corresponding word-level translation between the source and the target language sentences. It is widely used in the area of natural language processing, like machine translation, cross-language information retrieval, bilingual dictionary compilation. However, bilingual word alignment is a very difficult task involving many challenges such as morphology, syntax, semantics, human translation habits, and the inherent difference between English and Chinese. In this paper, a new algorithm is proposed. By adopting a multilayered matching and disambiguation strategy, the bilingual word-alignment task is transformed to an iterative solution of anchor word-pair. The positive experimental results of 93.5% precision, 77.3% recall, and 84.2% F-score show the algorithm´s effectiveness.