: NLP Vocabulary: post-editing

applied NLP > machine translation > post-editing

post-editing

The correction of raw machine-translated output by a human translator according to specific guidelines and quality criteria. (O’Brien, Towards predicting post-editing productivity, in Machine Translation, 2011)

As expected PE time varies considerably for different sentences even if outliers are removed. (Specia, Harris, Blain, Burchardt, Macketanz, Skadin, Negri & Turchi, 2017)
Blain et al. (2011) take a more qualitative approach to understanding postediting by introducing a measure based on postediting actions. (Góis & Martins, 2019)
Both PE and error annotations were performed by professional translators. (Specia, Harris, Blain, Burchardt, Macketanz, Skadin, Negri & Turchi, 2017)
Professional translators performed PE on every language pair. (Specia, Harris, Blain, Burchardt, Macketanz, Skadin, Negri & Turchi, 2017)
The translation quality and the amount of post-editing needed is closely related to the quality and nature of the original text. (Nagao, Tsujii & Nakamura, 1985)

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