Saeel Sandeep Nachane, Ojas Gramopadhye, et al.
EMNLP 2024
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.
Saeel Sandeep Nachane, Ojas Gramopadhye, et al.
EMNLP 2024
Wooseok Choi, Tommaso Stecconi, et al.
Advanced Science
Robert Farrell, Rajarshi Das, et al.
AAAI-SS 2010
Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence