Comparable Corpora And Computer-Assisted Translation

This book addresses the use of comparable corpora for computer-assisted translation. The first part of the book contains a state-of-the art of the techniques used for the extraction of bilingual lexicon from comparable corpora as well as a user-centered evaluation of these lexicons. The second part of the book details the experimentation of a new method for extracting lexicons from comparable corpora. The method is based on the compositionality principle. We also detail the experimentation of learning-to-rank algorithms for ranking the generated translations.

Although the usefulness of comparable corpora had been demonstrated in areas like machine translation or cross-lingual information retrieval, it had never been assessed for computer-assisted translation. Moreover, there is no book offering a state-of-the art of the techniques used in comparable corpora processing. The research, though addressing theoretical aspects, also has an applicative orientation since it was partly conducted in an industrial context.

Estelle Maryline Delpech holds a PhD in Computer Science from the University of Nantes in France, where she specialized in natural language processing and computer-aided translation. She is currently Chief Scientist at Nomao, a web and mobile app search engine company. Her research interests include multilingualism, computational linguistics, information extraction and data integration.