Date of Original Version

10-2012

Type

Conference Proceeding

Journal Title

Proceedings of the Tenth Conference of the Association for Machine Translation in the Americas

Rights Management

Copyright ATMA

Abstract or Description

As machine translation quality continues to improve, the idea of using MT to assist human translators becomes increasingly attractive. In this work, we discuss and provide empirical evidence of the challenges faced when adapting traditional MT systems to provide automatic translations for human post-editors to correct. We discuss the differences between this task and traditional adequacy-based tasks and the challenges that arise when using automatic metrics to predict the amount of effort required to post-edit translations. A series of experiments simulating a real-world localization scenario shows that current metrics under-perform on this task, even when tuned to maximize correlation with expert translator judgments, illustrating the need to rethink traditional MT pipelines when addressing the challenges of this translation task.

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Published In

Proceedings of the Tenth Conference of the Association for Machine Translation in the Americas.