Abstract
We describe a series o,ffive statistical models o,f the translation process and give algorithms,for
estimating the parameters o,f these models given a set o,f pairs o,f sentences that are translations
o,f one another. We define a concept o,f word-by-word alignment between such pairs o,f sentences.
For any given pair of such sentences each o,f our models assigns a probability to each of the
possible word-by-word alignments. We give an algorithm for seeking the most probable o,f these
alignments. Although the algorithm is suboptimal, the alignment thus obtained accounts well for
the word-by-word relationships in the pair o,f sentences. We have a great deal o,f data in French
and English from the proceedings o,f the Canadian Parliament. Accordingly, we have restricted
our work to these two languages; but we,feel that because our algorithms have minimal linguistic
content they would work well on other pairs o,f languages. We also ,feel, again because of the
minimal linguistic content o,f our algorithms, that it is reasonable to argue that word-by-word
alignments are inherent in any sufficiently large bilingual corpus.
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