  Current lexical simplification approaches rely heavily on heuristics and
corpus level features that do not always align with human judgment. We create a
human-rated word-complexity lexicon of 15,000 English words and propose a novel
neural readability ranking model with a Gaussian-based feature vectorization
layer that utilizes these human ratings to measure the complexity of any given
word or phrase. Our model performs better than the state-of-the-art systems for
different lexical simplification tasks and evaluation datasets. Additionally,
we also produce SimplePPDB++, a lexical resource of over 10 million simplifying
paraphrase rules, by applying our model to the Paraphrase Database (PPDB).
