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Permanent link (DOI): https://doi.org/10.7939/R38M5F

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Automatic speaker identification in novels Open Access

Descriptions

Other title
Subject/Keyword
Speaker identification
Speaker alternation pattern
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
He, Hua
Supervisor and department
Grzegorz Kondrak (Computing Science)
Denilson Barbosa (Computing Science)
Examining committee member and department
Stan Ruecker (English and Film Studies)
Mario A. Nascimento (Computing Science)
Davood Rafiei (Computing Science)
Grzegorz Kondrak (Computing Science)
Denilson Barbosa (Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2011-08-26T20:40:26Z
Graduation date
2011-11
Degree
Master of Science
Degree level
Master's
Abstract
Speaker identification is the task of attributing utterances to characters in literary narratives. Although only some of the utterances are explicitly attributed in novels, humans readers are able to determine the speakers of the remaining utterances because of their understanding of the plot. This dissertation proposes a method to automatically identify the speakers using supervised machine learning methods that utilize various text clues and a speaker alternation pattern. In addition, the method incorporates an unsupervised actor-topic model that aims to distinguish speakers depending on the content of their statements. The experimental results show that the method substantially outperforms a baseline method, and is competitive and more general when compared to previous approaches to the problem.
Language
English
DOI
doi:10.7939/R38M5F
Rights
License granted by Hua He (hhe@ualberta.ca) on 2011-08-26T01:15:12Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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