A systematic comparison of various statistical alignment models
Computational Linguistics
A statistical approach to language translation
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 1
Statistical Machine Translation
Statistical Machine Translation
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In this paper, we propose a novel approach to compare languages on the basis of parallel texts. Instead of using word lists or abstract grammatical characteristics to infer (phylogenetic) relationships, we use multilingual alignments of words in sentences to establish measures of language similarity. To this end, we introduce a new method to quickly infer a multilingual alignment of words, using the co-occurrence of words in a massively parallel text (MPT) to simultaneously align a large number of languages. The idea is that a simultaneous multilingual alignment yields a more adequate clustering of words across different languages than the successive analysis of bilingual alignments. Since the method is computationally demanding for a larger number of languages, we reformulate the problem using sparse matrix calculations. The usefulness of the approach is tested on an MPT that has been extracted from pamphlets of the Jehova's Witnesses. Our preliminary experiments show that this approach can supplement both the historical and the typological comparison of languages.