SimpleNets: Quality Estimation with Resource-Light Neural Networks
Gustavo Henrique Paetzold, Lucia Specia · 2016
We introduce SimpleNets: a resource-light solution to the sentence-level Quality Estimation task of WMT16 that combines Recurrent Neural Networks, word embedding models, and the principle of compositionality.The SimpleNets systems explore the idea that the quality of a translation can be derived from the quality of its n-grams.This approach has been successfully employed in Text Simplification quality assessment in the past.Our experiments show that, surprisingly, our models can learn more about a translation's quality by focusing on the original sentence, rather than on the translation itself.