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CD-ROM in back pocket comprises experimental results and executables. / System requirements: Unix workstation or PC with Windows 95 or Windows NT. The reports output by EPrep. can be viewed with a web browser such as Netscape or Microsoft Internet Explorer through the top level HTML page. / Bibliography: p. 251-261. / Computer data and programs / HTML reports, data and figures generated by EPrep / xxiv, 261 p. : ill. ; 30 cm. + 1 computer laser optical disk ; 4 3/4". / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Proposes a framework for automatic feature extraction called generalised pre-processor. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1999

CD-ROM in back pocket comprises experimental results and executables. / System requirements: Unix workstation or PC with Windows 95 or Windows NT. The reports output by EPrep. can be viewed with a web browser such as Netscape or Microsoft Internet Explorer through the top level HTML page. / Bibliography: p. 251-261. / Computer data and programs / HTML reports, data and figures generated by EPrep / xxiv, 261 p. : ill. ; 30 cm. + 1 computer laser optical disk ; 4 3/4". / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Proposes a framework for automatic feature extraction called generalised pre-processor. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1999

Thesis (Ph.D.)--Auburn University, 2005. / Abstract. Vita. Includes bibliographic references (ℓ. 97-100)

Thesis (M.S.)--Ohio University, August, 1984. / Title from PDF t.p.

Ph.D thesis (University of Western Australia (2006)). / Includes bibliographical references.

Thesis (M. Sc.)--University of Alberta, 2009. / Title from pdf file main screen (viewed on July 16, 2009). "A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science, Department of Mechanical Engineering, University of Alberta." Includes bibliographical references.

With the demand for recorded lectures to be made available as soon as possible, the University of Cape Town (UCT) needs to find innovative ways of removing bottlenecks in lecture capture workflow and thereby improving turn-around times from capture to publication. UCT utilises Opencast, which is an open source system to manage all the steps in the lecture-capture process. One of the steps involves manual trimming of unwanted segments from the beginning and end of video before it is published. These segments generally contain student chatter. The trimming step of the lecture-capture process has been identified as a bottleneck due to its dependence on staff availability. In this study, we investigate the potential of audio classification to automate this step. A classification model was trained to detect 2 classes: speech and non-speech. Speech represents a single dominant voice, for example, the lecturer, and non-speech represents student chatter, silence and other environmental sounds. In conjunction with the classification model, the first and last instances of the speech class together with their timestamps are detected. These timestamps are used to predict the start and end trim points for the recorded lecture. The classification model achieved a 97.8% accuracy rate at detecting speech from non-speech. The start trim point predictions were very positive, with an average difference of -11.22s from gold standard data. End trim point predictions showed a much greater deviation, with an average difference of 145.16s from gold standard data. Discussions between the lecturer and students, after the lecture, was predominantly the reason for this discrepancy.

Please read the abstract in the section 00front of this document. / Dissertation (M Eng (Electronic Engineering))--University of Pretoria, 2006. / Electrical, Electronic and Computer Engineering / unrestricted

No description available.