Paper: QuEst - A translation quality estimation framework

ACL ID P13-4014
Title QuEst - A translation quality estimation framework
Venue Annual Meeting of the Association of Computational Linguistics
Session System Demonstration
Year 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.