Private Access to Phrase Tables for Statistical Machine Translation
Some Statistical Machine Translation systems
never see the light because the owner of the
appropriate training data cannot release them,
and the potential user of the system cannot disclose
what should be translated. We propose a
simple and practical encryption-based method addressing this barrier.
The 50th Annual Meeting of the Association for Computational Linguistics, Jeju, Republic of Korea, 8-14 July, 2012.