  Recent approaches to automatically detect the speaker of an utterance of
direct speech often disregard general information about characters in favor of
local information found in the context, such as surrounding mentions of
entities. In this work, we explore stylistic representations of characters
built by encoding their quotes with off-the-shelf pretrained Authorship
Verification models in a large corpus of English novels (the Project Dialogism
Novel Corpus). Results suggest that the combination of stylistic and topical
information captured in some of these models accurately distinguish characters
among each other, but does not necessarily improve over semantic-only models
when attributing quotes. However, these results vary across novels and more
investigation of stylometric models particularly tailored for literary texts
and the study of characters should be conducted.
