Alignment of paragraphs in bilingual texts using bilingual dictionaries and dynamic programming

Authors:
Alexander Gelbukh;Grigori Sidorov
Affiliations:
Natural Language and Text Processing Laboratory, Center for Research in Computer Science, National Polytechnic Institute, Mexico City, Mexico;Natural Language and Text Processing Laboratory, Center for Research in Computer Science, National Polytechnic Institute, Mexico City, Mexico
Venue:
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Year:
2006

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Abstract

Parallel text alignment is a special type of pattern recognition task aimed to discover the similarity between two sequences of symbols. Given the same text in two different languages, the task is to decide which elements—paragraphs in case of paragraph alignment—in one text are translations of which elements of the other text. One of the applications is training training statistical machine translation algorithms. The task is not trivial unless detailed text understanding can be afforded. In our previous work we have presented a simple technique that relied on bilingual dictionaries but does not perform any syntactic analysis of the texts. In this paper we give a formal definition of the task and present an exact optimization algorithm for finding the best alignment.