The fact that the methods developed by [4] and<cite> [12]</cite> are based on a large, scarce lexical resources as WordNet, led us to raise the question "Could we have a similar performance with a simpler set of features which are easily obtainable for most languages?". Therefore we decided to build our regressors using only word length, frequency lists, lexical databases composed of school dictionaries and word embeddings models.