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Media type:
E-Article
Title:
What do post-editors correct? A fine-grained analysis of SMT and NMT errors
Contributor:
Alvarez-Vidal, Sergi;
Oliver, Antoni;
Badia, Toni
imprint:
Universitat Autonoma de Barcelona, 2021
Published in:Tradumàtica: tecnologies de la traducció
Language:
Not determined
DOI:
10.5565/rev/tradumatica.286
ISSN:
1578-7559
Origination:
Footnote:
Description:
<jats:p>The recent improvements in neural MT (NMT) have driven a shift from statistical MT (SMT) to NMT. However, to assess the usefulness of MT models for post-editing (PE) and have a detailed insight of the output they produce, we need to analyse the most frequent errors and how they affect the task. We present a pilot study of a fine-grained analysis of MT errors based on post-editors corrections for an English to Spanish medical text translated with SMT and NMT. We use the MQM taxonomy to compare the two MT models and have a categorized classification of the errors produced. Even though results show a great variation among post-editors’ corrections, for this language combination fewer errors are corrected by post-editors in the NMT output. NMT also produces fewer accuracy errors and errors that are less critical.</jats:p>