Measuring Phonological Complexity Using the Perfect Rhymes Dictionary (PeRDict)

Abstract

This paper examines links between perfect rhymes and text readability and decoding using a measure of English rhymes called the Perfect Rhymes Dictionary (PeRDict). PeRDict is based on the Carnegie Mellon University Pronouncing Dictionary (the CMUdict) and provides rhyme counts for ∼48,000 words in English and for the most frequent 1,000, 2,500, 5,000, and 10,000 rhymes within the dictionary as measured by the Corpus of American English (COCA). Two assessments of PeRDICT are presented. The first examines the strength of rhyme features to predict text readability in conjunction with word neighborhood density effects reported by the English Lexicon Project (ELP) and a word frequency measure. The second examines the strength of rhyme features to predict word decoding in conjunction with word neighborhood effects and a word frequency measure. In both assessments, the number of rhymes per word was predictive of text or word processing beyond features related to word neighborhood effects and word frequency. Word rhyme counts performed more strongly in predicting text processing versus word processing.