A naïve, salience-based method for speaker identification in fiction books
Kevin Glass, Shaun Bangay · 2007
This paper presents a salience-based technique for the anno-tation of directly quoted speech from fiction text. In particu-lar, this paper determines to what extent a naïve (without the use of complex machine learning or knowledge-based tech-niques) scoring technique can be used for the identification of the speaker of speech quotes. The presented technique makes use of a scoring technique, similar to that commonly found in knowledge-poor anaphora resolution research, as well as a set of hand-coded rules for the final identification of the speaker of each quote in the text. Speaker identification is shown to be achieved using three tasks: the identification of a speech-verb associated with a quote with a recall of 94.41%; the identifica-tion of the actor associated with a quote with a recall of 88.22%; and the selection of a speaker with an accuracy of 79.40%.