Knowles, Rebecca

Koehn, Philipp

In neural interactive translation prediction, a system provides translation suggestions (“auto-complete” functionality) for human translators. These translation suggestions may be rejected by the translator in predictable ways; being able to estimate confidence in the quality of translation suggestions could be useful in providing additional information for users of the system. We show that a very small set of features (which are already generated as byproducts of the process of translation prediction) can be used in a simple model to estimate confidence for interactive translation predictio

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Lightweight Word-Level Confidence Estimation for Neural Interactive Translation Prediction

https://www.pure.ed.ac.uk/ws/files/77106598/Lightweight_word_level_confidence_estimation_for_neural_interactive_translations_prediction.pdf

Lightweight Word-Level Confidence Estimation for Neural Interactive Translation Prediction

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