In this paper, we describe a fast algorithm for aligning sentences with their translations in a bilingual corpus. Existing efficient algorithms ignore word identities and only consider sentence length (Brown el al., 1991b; Gale and Church, 1991). Our algorithm constructs a simple statistical word-to-word translation model on the fly during alignment. We find the alignment that maximizes the probability of generating the corpus with this translation model. We have achieved an error rate of approximately 0.4% on Canadian Hansard data, which is a significant improvement over previous results. The algorithm is language independent.
Chen REF describes an algorithm that constructs a simple statistical word-to-word translation model on the fly during sentence alignment.
Aligning Sentences In Bilingual Corpora Using Lexical Information
Annual Meeting Of The Association For Computational Linguistics
Computer Science