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Multi-modal Video Ummarization Using Hidden Markov Models For Content-based Multimedia IndexingYasaroglu, Yagiz 01 January 2003 (has links) (PDF)
This thesis deals with scene level summarization of story-based videos. Two different approaches for story-based video summarization are investigated. The first approach probabilistically models the input video and identifies scene boundaries using the same model. The second approach models scenes and classifies scene types
by evaluating likelihood values of these models. In both approaches, hidden Markov models are used as the probabilistic modeling tools. The first approach also exploits the relationship between video summarization and video production, which is briefly explained, by means of content types. Two content types are defined, dialog driven and action driven content, and the need to define such content types is emonstrated
by simulations. Different content types use different hidden Markov models and
features. The selected model segments input video as a whole. The second approach models scene types. Two types, dialog scene and action scene, are defined with different features and models. The system classifies fixed sized partitions of the video as either of the two scene types, and segments partitions separately according to their scene types. Performance of these two systems are compared against a iv
deterministic video summarization method employing clustering based on visual properties and video structure related rules. Hidden Markov model based video summarization using content types enjoys the highest performance.
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The Markov-switching vector error correction model: dynamics, bayesian inference, and application to the spot and forward Swiss Franc, US Dollar exchange ratesFrei, Lukas January 2007 (has links)
Zugl.: Basel, Univ., Diss., 2007
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Phoneme duration modelling for speaker verificationVan Heerden, Charl Johannes. January 2009 (has links)
Thesis (M.Eng.(Computer Engineering)--University of Pretoria, 2008. / Summaries in Afrikaans and English. Includes bibliographical references.
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Exploration and optimization of noise reduction algorithms for speech recognition in embedded devices /Setiawan, Panji. January 2009 (has links)
Zugl.: München, Universiẗat der Bundeswehr, Diss., 2009.
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An ensemble speaker and speaking environment modeling approach to robust speech recognitionTsao, Yu. January 2008 (has links)
Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Lee, Chin-Hui; Committee Member: Anthony Joseph Yezzi; Committee Member: Biing-Hwang (Fred) Juang; Committee Member: Mark Clements; Committee Member: Ming Yuan. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Soft margin estimation for automatic speech recognitionLi, Jinyu. January 2008 (has links)
Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Dr. Chin-Hui Lee; Committee Member: Dr. Anthony Joseph Yezzi; Committee Member: Dr. Biing-Hwang (Fred) Juang; Committee Member: Dr. Mark Clements; Committee Member: Dr. Ming Yuan. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Automatic accompaniment of vocal melodies in the context of popular musicCao, Xiang. January 2009 (has links)
Thesis (M. S.)--Music, Georgia Institute of Technology, 2009. / Committee Chair: Chordia, Parag; Committee Member: Freeman, Jason; Committee Member: Weinberg, Gil.
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When God becomes your enemy the theology of the complaint Psalms /Fløysvik, Ingvar. January 1994 (has links)
Thesis (S.T.D.)--Concordia Seminary, 1994. / Includes Hebrew text of each Psalm with translation. Includes bibliographical references (leaves 212-229).
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Regime-basierte Modellansätze zur Identifikation periodisch platzender VermögenspreisblasenAnaswah, Nael al- January 2007 (has links)
Zugl.: Münster, Univ., Diss., 2007.
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Statistical optimization of acoustic models for large vocabulary speech recognitionHu, Rusheng, January 2006 (has links)
Thesis (Ph. D.) University of Missouri-Columbia, 2006. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on August 2, 2007) Includes bibliographical references.
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