Information and Knowledge Society

Machine Translation: A Concept for Machine Translation Evaluation and Detection

Doctoral Programme on the Information and Knowledge Society
18/05/2015

Author: Joaquim Moré López
Programme: Doctoral Programme on the Information and Knowledge Society
Language: English
Supervisor: Dr Salvador Climent Roca

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Summary

Machine translationness (MTness) is the linguistic phenomena that make machine translations distinguishable from human translations. This thesis introduces MTness as a research object and presents an MT evaluation method based on determining whether the translation is machinelike instead of determining its humanlikeness as in current evaluation approaches. The method rates the MTness of a translation with a metric, the MTS (Machine Translationness Score). The MTS calculation is in accordance with the results of an experimental study on machine translation perception by common people. MTS proved to correlate well with human ratings on translation quality. Besides, our approach allows the performance of cheap evaluations since expensive resources (e.g. reference translations, training corpora) are not needed. Machine translationness ratings can be applied for other uses beyond machine translation evaluation (plagiarism and other forms of cheating, detection of unsupervised MT documents published on the Web, etc.).