Assessing Relative Sentence Complexity using an Incremental CCG Parser

Given a pair of sentences, we present computational models to assess if one sentence is simpler to read than the other. While existing models explored the usage of phrase structure features using a non-incremental parser, experimental evidence suggests that the human language processor works incrementally. We empirically evaluate if syntactic features from an incremental CCG parser are more useful than features from a non-incremental phrase structure parser. Our evaluation on Simple and Standard Wikipedia sentence pairs suggests that incremental CCG features are indeed more useful than phrase structure features achieving 0.44 points gain in performance. Incremental CCG parser also gives significant improvements in speed (12 times faster) in comparison to the phrase structure parser. Furthermore, with the addition of psycholinguistic features, we achieve the strongest result to date reported on this task. Our code and data can be downloaded from https://github. com/bharatambati/sent-compl.