Simona Rabinovici-Cohen, Naomi Fridman, et al.
Cancers
Machine Translation of arbitrary input is difficult, but the output quality can be improved significantly if writers create documents with MT in mind. This article deals with "MTranslatability" -translatability of texts by MT systems. It identifies characteristics of text that decrease MTranslatability and suggests ways to improve them. It also illustrates the effect of writing for MTranslatability by showing before-and-after pictures of output from various commercially available MT systems, and gives an overview of tools that help identify and correct the problems.
Simona Rabinovici-Cohen, Naomi Fridman, et al.
Cancers
Jehanzeb Mirza, Leonid Karlinsky, et al.
NeurIPS 2023
David W. Jacobs, Daphna Weinshall, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gaku Yamamoto, Hideki Tai, et al.
AAMAS 2008