Thesis (M.Eng.(Computer Engineering))--University of Pretoria, 1999. / Summaries in Afrikaans and English. Includes bibliographic references.

Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, March 2005. / Thesis Advisor(s): James F Ehlert. Includes bibliographical references (p. 65-66). Also available online.

Thesis (M.S.) -- Worcester Polytechnic Institute. / Keywords: automobile; noise reduction; passing vehicle noise; hands-free Includes bibliographical references (p. 89-91).

Thesis (MScIng)--University of Stellenbosch, 2005. / Bibliography. Also available via the Internet.

Thesis (MScIng)--University of Stellenbosch, 2008. / Bibliography. Also available via the Internet.

Thesis (M.S.)--University of Texas at Dallas, 2008. / Includes vita. Includes bibliographical references (leaves 47-49)

Thesis (M.S.)--University of Texas at Dallas, 2008. / Includes vita. Includes bibliographical references (leaves 36-37)

Thesis (Master Diploma (Technology))--Cape Technikon, Cape Town,1993 / A study into the practical implementation of Speech Recognition for the purposes of Data Capturing within Telkom SA. is described. As datacapturing is increasing in demand a more efficient method of capturing is sought. The technology relating to Speech recognition is herein examined and practical gnidelines for selecting a Speech recognition system are described. These guidelines are used to show how commercially available systems can be evaluated. Specific tests on a selected speech recognition system are described, relating to the accuracy and adaptability of the system. The results obtained illustrate why at present speech recognition systems are not advisable for the purpose of Data capturing. The results also demonstrate how the selection of keywords words can affect system performance. Areas of further research are highlighted relating to recognition performance and vocabulary selection.

Submitted in fulfillment of the academic requirements for the degree of Master of Technology in Electrical Engineering in the Department of Electronic Engineering, Faculty of Engineering, ML Sultan Technikon of Durban in South Africa, March 2002. / The use of speaker recognition technology in interactive voice response and electronic commerce systems has been limited. This is due to the lack of research attention and published results when compared to all the other areas of speech recognition technologies / M

This dissertation investigates the cost-complexity-performance relationship between two automatic language identification systems. The first is a state-of-the-art archi¬tecture, trained on about three hours of phonetically hand-labelled telephone speech obtained from the recognised OGLTS corpus. The second system, introduced by our¬selves, is a simpler design with a smaller, less complex parameter space. It is a vector quantisation-based approach which bears some resemblance to a system suggested by Sugiyama. Though trained on the same data, it has no need for any labels and is therefore less costly. A number of experiments are performed to find quasi-optimal parameters for the two systems. In further experiments the systems are evaluated and compared on a set of ten two-language tasks, spanning five languages. The more com¬plex system is shown to have a substantial performance advantage over the simpler design - 81% versus 65% on 40 seconds of speech. However, both results are well under reported state-of-the-art performance of 94% and would suggest that our systems can benefit from additional attention to implementation detail and optimisation of various parameters. Given the above, our suggested architecture may potentially provide an adequate solution where the high development cost associated with state-of-the-art technology and the necessary training corpora are prohibitive. / Dissertation (M Eng (Computer Engineering))--University of Pretoria, 2006. / Electrical, Electronic and Computer Engineering / unrestricted