QuEst - A translation quality estimation framework
Lucia Specia, Kashif Ur Rehman Shah, José G. C. de Souza, Trevor Cohn · White Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 2013
We describe QUEST, an open source framework for machine translation quality estimation. The framework allows the ex-traction of several quality indicators from source segments, their translations, exter-nal resources (corpora, language models, topic models, etc.), as well as language tools (parsers, part-of-speech tags, etc.). It also provides machine learning algorithms to build quality estimation models. We benchmark the framework on a number of datasets and discuss the efficacy of fea-tures and algorithms. 1