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Comparable Corpora and Computer-assisted Translation (Hardcover)
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Comparable Corpora and Computer-assisted Translation (Hardcover)
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Computer-assisted translation (CAT) has always used translation
memories, which require the translator to have a corpus of previous
translations that the CAT software can use to generate bilingual
lexicons. This can be problematic when the translator does not have
such a corpus, for instance, when the text belongs to an emerging
field. To solve this issue, CAT research has looked into the
leveraging of comparable corpora, i.e. a set of texts, in two or
more languages, which deal with the same topic but are not
translations of one another. This work had two primary objectives.
The first is to assess the input of lexicons extracted from
comparable corpora in the context of a specialized human
translation task. The second objective is to identify
bilingual-lexicon-extraction methods which best match the
translators' needs, determining the current limits of these
techniques and suggesting improvements. The author focuses, in
particular, on the identification of fertile translations, the
management of multiple morphological structures, and the ranking of
candidate translations. The experiments are carried out on two
language pairs (English-French and English-German) and on
specialized texts dealing with breast cancer. This research puts
significant emphasis on applicability - methodological choices are
guided by the needs of the final users. This book is organized in
two parts: the first part presents the applicative and scientific
context of the research, and the second part is given over to
efforts to improve compositional translation. The research work
presented in this book received the PhD Thesis award 2014 from the
French association for natural language processing (ATALA).
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