Thesis (Ph. D.)--University of Washington, 2007. / Vita. Includes bibliographical references (p. 174-191).

No description available.

Distributional models of semantics have proven themselves invaluable both in cognitive modelling of semantic phenomena and also in practical applications. For example, they have been used to model judgments of semantic similarity (McDonald, 2000) and association (Denhire and Lemaire, 2004; Griffiths et al., 2007) and have been shown to achieve human level performance on synonymy tests (Landuaer and Dumais, 1997; Griffiths et al., 2007) such as those included in the Test of English as Foreign Language (TOEFL). This ability has been put to practical use in automatic thesaurus extraction (Grefenstette, 1994). However, while there has been a considerable amount of research directed at the most effective ways of constructing representations for individual words, the representation of larger constructions, e.g., phrases and sentences, has received relatively little attention. In this thesis we examine this issue of how to compose meanings within distributional models of semantics to form representations of multi-word structures. Natural language data typically consists of such complex structures, rather than just individual isolated words. Thus, a model of composition, in which individual word meanings are combined into phrases and phrases combine to form sentences, is of central importance in modelling this data. Commonly, however, distributional representations are combined in terms of addition (Landuaer and Dumais, 1997; Foltz et al., 1998), without any empirical evaluation of alternative choices. Constructing effective distributional representations of phrases and sentences requires that we have both a theoretical foundation to direct the development of models of composition and also a means of empirically evaluating those models. The approach we take is to first consider the general properties of semantic composition and from that basis define a comprehensive framework in which to consider the composition of distributional representations. The framework subsumes existing proposals, such as addition and tensor products, but also allows us to define novel composition functions. We then show that the effectiveness of these models can be evaluated on three empirical tasks. The first of these tasks involves modelling similarity judgements for short phrases gathered in human experiments. Distributional representations of individual words are commonly evaluated on tasks based on their ability to model semantic similarity relations, e.g., synonymy or priming. Thus, it seems appropriate to evaluate phrase representations in a similar manner. We then apply compositional models to language modelling, demonstrating that the issue of composition has practical consequences, and also providing an evaluation based on large amounts of natural data. In our third task, we use these language models in an analysis of reading times from an eye-movement study. This allows us to investigate the relationship between the composition of distributional representations and the processes involved in comprehending phrases and sentences. We find that these tasks do indeed allow us to evaluate and differentiate the proposed composition functions and that the results show a reasonable consistency across tasks. In particular, a simple multiplicative model is best for a semantic space based on word co-occurrence, whereas an additive model is better for the topic based model we consider. More generally, employing compositional models to construct representations of multi-word structures typically yields improvements in performance over non-compositonal models, which only represent individual words.

The thesis presents a way to apply process algebra to computational linguistics. We are interested in how contexts can affect or contribute to language understanding and model the phenomena as a system of communicating processes to study the interaction between them in detail. For this purpose, we turn to the pie-calculus and investigate how communicating processes may be defined. While investigating the computational grounds of communication and concurrency,we devise a graphical representation for processes to capture the structure of interaction between them. Then, we develop a logic, combinatory intuitionistic linear logic with equality relation, to specify communicating processes logically. The development enables us to study Situation Semantics with process algebra. We construct semantic objects employed in Situation Semantics in the pi-calculus and then represent them in the logic. Through the construction,we also relate Situation Semantics with the research on the information flow, Channel Theory, by conceiving of linear logic as a theory of the information flow. To show how sentences can be parsed as the result of interactions between processes, we present a concurrent chart parser encoded in the pi-calculus. We also explain how a semantic representation can be generated as a process by the parser. We conclude the thesis by comparing the framework with other approaches.

Thesis (Honors)--College of William and Mary, 2009. / Includes bibliographical references (leaves 28-29). Also available via the World Wide Web.

Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xv, 268 p.; also includes graphics. Includes abstract and vita. Advisor: Chris Brew, Dept. of Linguistics. Includes bibliographical references (p. 252-266) and index.

This paper describes an experiment where open and directed prompts were alternated when collecting speech data for the deployment of a call-routing application. The experiment tested whether open and directed prompts resulted in any differences with respect to the filled pauses exhibited by the callers, which is interesting in the light of the “many-options” hypothesis of filled pause production. The experiment also investigated the effects of the prompts on utterance form and meaning of the callers.

Thesis (Ph. D.)--University of North Texas, Dec., 2009. / Title from title page display. Includes bibliographical references.

Thesis (Ph.D.(Mechanical Engineering))--University of Pretoria, 2000. / Title from opening screen (viewed 10th March, 2005). Summaries in Afrikaans and English. Includes bibliographical references.

Thesis (M.S.)--University of North Texas, Dec., 2008. / Title from title page display. Includes bibliographical references.