Abstract
Despite the impressive amount of recent studies devoted to improving the state of the art of Machine Translation (MT), Computer Assisted Translation (CAT) tools remain the preferred solution of human translators when publication quality is of concern. In this paper, we present our perspectives on improving the commercial bilingual concordancer TransSearch, a Web-based service whose core technology mainly relies on sentence-level alignment. We report on experiments which show that it can greatly benefit from statistical word-level alignment. © 2009 Springer Berlin Heidelberg.
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CITATION STYLE
Bourdaillet, J., Huet, S., Gotti, F., Lapalme, G., & Langlais, P. (2009). Enhancing the bilingual concordancer transSearch with word-level alignment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5549 LNAI, pp. 27–38). https://doi.org/10.1007/978-3-642-01818-3_6
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