Thesis (Ph. D., Education)--University of Idaho, June 2007. / Major professor: Martha C. Yopp. Includes bibliographical references (leaves 165-178). Also available online (PDF file) by subscription or by purchasing the individual file.

Thesis (Ed. D.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains x, 133 p. : map. Includes abstract. Includes bibliographical references (p. 93-100).

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of North Carolina at Greensboro, 2006. / Title from PDF title page screen. Advisor: Samuel D. Miller ; submitted to the School of Education. Includes bibliographical references (p. 110-120)

This paper outlines and implements a systematic approach to the establishment, investigation, and testing of distances and topologies on language spaces. The collection of all languages over a given number of symbols forms a semiring, appropriately termed a language space. Families of languages are defined by interrelations among words. The traditional classification begins with the syntax rules or grammar of the language, that is, the word-transformations by which the entire language can be produced from a single axiom, or starting word. The study of distances between languages as objects and of the topologies induced by language distances upon spaces of languages has been of a limited character. Known language distances introduce topologically awkward features into a language space, such as total disconnectedness. This dissertation examines the topologies induced by three language distances, the effect that each one has upon the notion of a random language, and discusses continuity and word-distribution of structure-preserving language transformations, i.e., morphisms. This approach starts from metric-like requirements, but adduces an additional condition intuitively appropriate to gauging language distance. At the same time, strict, i.e. non-metric pseudometrics are admitted as possible language distance functions, and these are investigated by the use of metric quotient spaces. The study of the notion of randomness implied by the topology induced by such a pseudo-metric on a language space offers insight into the structure of language spaces and verifies the viability of the pseudo-metric. Three language pseudo-metrics are studied in this dissertation: a version of the most commonlyused (Cantor) word metric; an upper-density (Besicovitch) pseudo-metric borrowed from the study of cellular automata; and an adaptation and normalization of topological entropy, each evaluated on the symmetric set-difference between languages. It is shown that each of these distances induces a distinct topology on the space of languages. The topology induced by Cantor distance is compact and totally disconnected, the topologies induced by the other two are non-compact, with entropic distance resulting in a topology that is the strict refinement of the Besicovitch topology, enhancing the picture of the smaller languages in the Besicovitch topology. It is also shown that none of the three topologies gives quantitative expression to the distinction between regular and linear languages, although, using Martin-Lof randomness tests, it is shown that each pseudo-metric is associated with a new notion of a random language. A classification of language mappings is introduced, with the aim of identifying those which best preserve the structure of languages under specific topologies. There are results regarding continuity of mappings, the matrix representation of the pre-image of certain morphisms, and the formal expressions of the probability distribution of the image of certain morphism. The continuity of an injective morphism on its image is demonstrated under limited conditions. Finally, the questions which this approach leaves open are detailed. While basic facts about a permutation-invariant version of symmetric set difference are shown, this has yet to be fully elaborated. The outline is presented for a metric which distinguishes between regular and linear languages by brute force. Syntactic and as algebraic topological continuations of this approach await investigation. A variation of the Cantor distance is introduced, and this induces a non-Cantor topology on a language space. In summary, this dissertation demonstrates that it is possible to systematically topologize the formal language space, and, having done so, to determine the major effects this has upon the notion of random languages and upon language morphisms.

The purpose of Language Identification (LID) is to identify a specific language from a spoken utterance, automatically. Language-specific characteristics are always associated with different languages. Most existing LID approaches utilise a statistical modelling process with common acoustic/phonotactic features to model specific languages while avoiding any language-specific knowledge. Great successes have been achieved in this area over past decades. However, there is still a huge gap between these languageindependent methods and the actual language-specific patterns. It is extremely useful to address these specific acoustic or semantic construction patterns, without spending huge labour on annotation which requires language-specific knowledge. Inspired by this goal, this research focuses on the language-feature dependency. Several practical methods have been proposed. Various features and modelling techniques have been studied in this research. Some of them carry out additional language-specific information without manual labelling, such as a novel duration modelling method based on articulatory features, and a novel Frequency-Modulation (FM) based feature. The performance of each individual feature is studied for each of the language-pair combinations. The similarity between languages and the contribution in identifying a language by using a particular feature are defined for the first time, in a quantitative style. These distance measures and languagedependent contributions become the foundations of the later-presented frameworks ?? language-dependent weighting and hierarchical language identification. The latter particularly provides remarkable flexibility and enhancement when identifying a relatively large number of languages and accents, due to the fact that the most discriminative feature or feature-combination is used when separating each of the languages. The proposed systems are evaluated in various corpora and task contexts including NIST language recognition evaluation tasks. The performances have been improved in various degrees. The key techniques developed for this work have also been applied to solve a different problem other than LID ?? speech-based cognitive load monitoring.

The purpose of Language Identification (LID) is to identify a specific language from a spoken utterance, automatically. Language-specific characteristics are always associated with different languages. Most existing LID approaches utilise a statistical modelling process with common acoustic/phonotactic features to model specific languages while avoiding any language-specific knowledge. Great successes have been achieved in this area over past decades. However, there is still a huge gap between these languageindependent methods and the actual language-specific patterns. It is extremely useful to address these specific acoustic or semantic construction patterns, without spending huge labour on annotation which requires language-specific knowledge. Inspired by this goal, this research focuses on the language-feature dependency. Several practical methods have been proposed. Various features and modelling techniques have been studied in this research. Some of them carry out additional language-specific information without manual labelling, such as a novel duration modelling method based on articulatory features, and a novel Frequency-Modulation (FM) based feature. The performance of each individual feature is studied for each of the language-pair combinations. The similarity between languages and the contribution in identifying a language by using a particular feature are defined for the first time, in a quantitative style. These distance measures and languagedependent contributions become the foundations of the later-presented frameworks ?? language-dependent weighting and hierarchical language identification. The latter particularly provides remarkable flexibility and enhancement when identifying a relatively large number of languages and accents, due to the fact that the most discriminative feature or feature-combination is used when separating each of the languages. The proposed systems are evaluated in various corpora and task contexts including NIST language recognition evaluation tasks. The performances have been improved in various degrees. The key techniques developed for this work have also been applied to solve a different problem other than LID ?? speech-based cognitive load monitoring.

The focus of this thesis is the comparison of languages and the reduction of automata used in network traffic monitoring. In this work, several approaches for approximate (language non-preserving) reduction of automata and comparison of their languages are proposed. The reductions are based on either under-approximating the languages of automata by pruning their states, or over-approximating the language by introducing new self-loops (and pruning redundant states later). The proposed approximate reduction methods and the proposed probabilistic distance utilize information from a network traffic. Formal guarantees with respect to a model of network traffic, represented using a probabilistic automaton are provided. The methods were implemented and evaluated on automata used in network traffic filtering.

This thesis deals with providing feedback in Czech lessons as a second language in a distance environment. Using a descriptive analysis of the transcripts of four video recordings of Czech for foreigners, we focused our attention on the places where teachers provided feedback to students. The aim of this work was to find out what means teachers use for this. We were also interested in whether the online environment had any effect on the provision of feedback. A questionnaire was developed to assess teachers' views on providing feedback. Key words: Feedback, Czech as a foreign language, distance learning, online teaching, audiovisual context, nonverbal communication, e-learning.