no code implementations • NAACL 2018 • Nicola Ueffing, Jos{\'e} G. C. de Souza, Gregor Leusch
In this paper, we present different approaches: The first one is a Random Forest (RF) model that explores hand-crafted, robust features, which are a mix of established features commonly used in Machine Translation Quality Estimation (MTQE) and new features developed specifically for our task.
no code implementations • SEMEVAL 2016 • Duygu Ataman, Jos{\'e} G. C. de Souza, Marco Turchi, Matteo Negri
Cross-Lingual Semantic Textual Similarity Machine Translation +6