Issue #84 – Are Neural Machine Translation Systems Good Estimators of Quality?

04 Jun20

Author: Prof. Lucia Specia, Professor of Natural Language Processing, Imperial College London (also to ADAPT/Dublin City University and University of Sheffield)

This week, we are delighted to have a guest post from Prof. Lucia Specia of Imperial College London, and laterally the University of Sheffield and our own alma mater, Dublin City University. Prof. Specia is one of the world’s preeminent experts on the topic of quality estimation for machine translation, and in her post, she takes a look at how this is being applied in the context of Neural MT. It’s a timely post, and this topic will also be covered in our upcoming webinar on future trends in machine translation. Enjoy reading!

Overview

In this post, we will look into the task of predicting the quality of machine translation, its applications, and how research in this area has been reshaped in the context of neural machine translation. More specifically, we will discuss the shift from quality estimation models devised independently from the machine translation systems, to models that resemble neural machine translation systems, and finally to using the neural machine translation system itself
To finish reading, please visit source site