title: Automatic Attribution of Quoted Speech in Literary Narrative
abstract: We describe a method for identifying the speakers of quoted speech in natural-language textual stories. We have assembled a corpus of more than 3,000 quotations, whose speakers (if any) are manually identiﬁed, from a collection of 19th and 20th century literature by six authors. Using rule-based and statistical learning, our method identiﬁes candidate characters, determines their genders, and attributes each quote to the most likely speaker. We divide the quotes into syntactic classes in order t