A Computational Analysis of the Voices of Shakespeare's Characters

Abstract

In this paper we propose a study of a relatively novel problem in authorship attribution research: that of classifying the stylome of characters in a literary work. We choose as a case study the plays of William Shakespeare, presumably the most renowned and respected dramatist in the history of literature. Previous research in the field of authorship attribution has shown that the writing style of an author can be characterized and distinguished from that of other authors automatically. The question we propose to answer is a related but different one: can the styles of different characters be distinguished? We aim to verify in this way if an author managed to create believable characters with individual styles, and focus on Shakespeare's iconic characters. We present our experiments using various features and models, including an SVM and a neural network, show that characters in Shakespeare's plays can be classified with up to 50% accuracy.