While there has been much work on computational models to predict readability based on the lexical, syntactic and discourse properties of a text, there are also interesting open questions about how computer generated text should be evaluated with target populations. In this paper, we compare two offline methods for evaluating sentence quality, magnitude estimation of acceptability judgements and sentence recall. These methods differ in the extent to which they can differentiate between surface level fluency and deeper comprehension issues. We find, most importantly, that the two correlate. Magnitude estimation can be run on the web without supervision, and the results can be analysed automatically. The sentence recall methodology is more resource intensive, but allows us to tease apart the fluency and comprehension issues that arise.
|Title of host publication||Proceedings of the NAACL 2012 Workshop on Predicting and Improving Text Readability (PITR 2012)|
|Number of pages||8|
|Publication status||Published - 2012|
Siddharthan, A., & Katsos, N. (2012). Offline Sentence Processing Measures for testing Readability with Users. In Proceedings of the NAACL 2012 Workshop on Predicting and Improving Text Readability (PITR 2012) (pp. 17-24). ACL. http://www.aclweb.org/anthology/W/W12/W12-2203.pdf