R. Sebastian, M. Weise, et al.
ECPPM 2022
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.
R. Sebastian, M. Weise, et al.
ECPPM 2022
Albert Atserias, Anuj Dawar, et al.
Journal of the ACM
Haoran Liao, Derek S. Wang, et al.
Nature Machine Intelligence
Sashi Novitasari, Takashi Fukuda, et al.
INTERSPEECH 2025