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 of languages. We have a great deal of data in French and English from the proceedings of the Canadian Parliament. Although the algorithm is suboptimal, the alignment thus obtained accounts well for the word-by-word relationships in the pair of sentences. We give an algorithm for seeking the most probable of these alignments. For any given pair of such sentences each of our models assigns a probability to each of the possible word-by-word alignments. We define a concept of word-by-word alignment between such pairs of sentences. We describe a series of five statistical models of the translation process and give algorithms for estimating the parameters of these models given a set of pairs of sentences that are translations of one another.
