Thesis (Ph. D.)--University of Washington, 2002. / Vita. Includes bibliographical references (p. 110-123).

Thesis (Ph. D.)--Ohio State University, 2004. / Title from first page of PDF file. Document formatted into pages; contains xv, 253 p.; also includes graphics. Includes abstract and vita. Advisor: Chris Brew, Dept. of Linguistics. Includes bibliographical references (p. 245-253).

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In this thesis, I examine human-like language generation from a visual input head-on, exploring how people refer to visible objects in the real world. Using previous work and the studies from this thesis, I propose an algorithm that generates humanlike reference to visible objects. Rather than introduce a general-purpose REG algorithm, as is tradition, I address the sorts of properties that visual domains in particular make available, and the ways that these must be processed in order to be used in a referring expression algorithm. This method uncovers several issues in generating human-like language that have not been thoroughly studied before. I focus on the properties of color, size, shape, and material, and address the issues of algorithm determinism and how speaker variation may be generated; unique identification of objects and whether this is an appropriate goal for generating humanlike reference; atypicality and the role it plays in reference; and multi-featured values for visual attributes. Technical contributions from this thesis include (1) an algorithm for generating size modifiers from features in a visual scene; and (2) a referring expression generation algorithm that generates structures for varied, human-like reference.

Many theories of humour claim that incongruity is an essential ingredient of humour. How- ever this idea is poorly understood and little work has been done in computational humour to quantify it. For example classifiers which attempt to distinguish jokes from regular texts tend to look for secondary features of humorous texts rather than for incongruity. Similarly most joke generators attempt to recreate structural patterns found in example jokes but do not deliberately endeavour to create incongruity. As in previous research, this thesis develops classifiers and a joke generator which attempt to automatically recognize and generate a type of humour. However the systems described here differ from previous programs because they implement a model of a certain type of humorous incongruity. We focus on a type of register humour we call lexical register jokes in which the tones of individual words are in conflict with each other. Our goal is to create a semantic space that reflects the kind of tone at play in lexical register jokes so that words that are far apart in the space are not simply different but exhibit the kinds of incongruities seen in lexical jokes. This thesis attempts to develop such a space and various classifiers are implemented to use it to distinguish lexical register jokes from regular texts. The best of these classifiers achieved high levels of accuracy when distinguishing between a test set of lexical register jokes and 4 different kinds of regular text. A joke generator which makes use of the semantic space to create original lexical register jokes is also implemented and described in this thesis. In a test of the generator, texts that were generated by the system were evaluated by volunteers who considered them not as humorous as human-made lexical register jokes but significantly more humorous than a set of control (i.e.non- joke) texts. This was an encouraging result which suggests that the vector space is somewhat successful in discovering lexical differences in tone and in modelling lexical register jokes.

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Thesis (M.S.)--Brigham Young University. Dept. of Computer Science, 2006. / Includes bibliographical references (p. 50-53).

Thesis (Ph. D.)--Oregon Graduate Center, 1988.

Thesis (Ph.D. Computer Science)--University of Waikato, 2007. / Title from PDF cover (viewed May 8, 2008) Includes bibliographical references (p. 191-195)

Thesis (doctoral)--Universität des Saarlandes, 2006. / Includes bibliographical references (p. 327-350).