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The taraXÜ corpus of human-annotated machine translations
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014)
Abstract
Human translators are the key to evaluating machine translation (MT) quality and also to addressing the so far unanswered question when and how to use MT in professional translation workflows. This paper describes the corpus developed as a result of a detailed large scale human evaluation consisting of three tightly connected tasks: ranking, error classification and post-editing.