A complete description of the features used for word-level MTQE can be found in Section 2 of the paper by<cite> Esplà-Gomis et al. (2015)</cite> . Following the approach by<cite> Esplà-Gomis et al. (2015)</cite> , the perceptron was built with a single hidden layer containing the same number of nodes as the number of features; this was the best performing architecture in the preliminary experiments.