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Features From Frequency: Authorship and Stylistic Analysis Using Repetitive Sound

To be able to capture repetitive sound in a feature for authorship and stylistic analysis is of great interest. In this paper, we present the functional n-gram as a feature well suited to the analysis of poetry and other sound-sensitive material, working toward stylistics based on sound rather than text. Using Support Vector Machines (SVM) for text classification, we extend the expression of our results from a single marginal distance or a binary yes/no decision to a more flexible receiveroperator characteristic curve. We apply the same feature methodology to Principal Component Analysis (PCA) in order to validate PCA and to explore its expressive potential. Having classified texts, we return to the most useful features and attempt to explain their relationship to the text in linguistic and literary terms.