A Corpus of Machine Translation Errors Extracted from Translation Students Exercises
Guillaume Wisniewski, Natalie Kübler, François Yvon · 2014
In this paper, we present a freely available corpus of automatic translations accompanied with post-edited versions, annotated with labels identifying the different kinds of errors made by the MT system.These data have been extracted from translation students exercises that have been corrected by a senior professor.This corpus can be useful for training quality estimation tools and for analyzing the types of errors made MT system.