%0 Conference Proceedings %T Towards contextual adaptation for any-text translation %A Gong, Li %A Max, Aurélien %A Yvon, François %S Proceedings of the 9th International Workshop on Spoken Language Translation: Papers %D 2012 %8 dec 6 7 %C Hong Kong, Table of contents %F gong-etal-2012-towards %X Adaptation for Machine Translation has been studied in a variety of ways, using an ideal scenario where the training data can be split into ”out-of-domain” and ”in-domain” corpora, on which the adaptation is based. In this paper, we consider a more realistic setting which does not assume the availability of any kind of ”in-domain” data, hence the name ”any-text translation”. In this context, we present a new approach to contextually adapt a translation model onthe-fly, and present several experimental results where this approach outperforms conventionaly trained baselines. We also present a document-level contrastive evaluation whose results can be easily interpreted, even by non-specialists. %U https://aclanthology.org/2012.iwslt-papers.20 %P 292-299