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dc.contributor.advisorZhao, Yunxineng
dc.contributor.authorZhang, Yieng
dc.date.issued2012eng
dc.date.submitted2012 Falleng
dc.descriptionTitle from PDF of title page (University of Missouri--Columbia, viewed on March 5, 2013).eng
dc.descriptionThe entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.eng
dc.descriptionDissertation advisor: Dr. Yunxin Zhaoeng
dc.descriptionIncludes bibliographical references.eng
dc.descriptionVita.eng
dc.descriptionPh. D. University of Missouri--Columbia 2012.eng
dc.descriptionDissertations, Academic -- University of Missouri--Columbia -- Computer science.eng
dc.description"December, 2012"eng
dc.description.abstractClean speech signal is often accompanied by various kinds of interferences, such as background noise, reverberation, and competing speech. These interferences degrade speech perceptual quality and intelligibility, and hamper speech technology applications. Conventional speech enhancement methods enhance the acoustic magnitude spectrum and use the corrupted speech phase spectrum for signal recovery. Besides, acoustic frequency domain subtraction methods often introduce large speech distortions, which degrade the enhancement performance. We propose a novel spectral subtraction method for noisy speech enhancement (MRISS) to enhance magnitude as well as phase through spectral subtraction. We investigate applying the MRISS algorithm to the speech dereverberation task to recover the reverberant speech. We investigate DOA based blind speech separation method under clean, noisy and reverberant conditions. We propose using ALMM to fit the subband IPD data to improve the DOA estimation, and propose using a log likelihood criterion to estimate the source numbers. Both subjective and objective measurements proved that the proposed methods obtained better results over state-of-art techniques on TIMIT dataset.eng
dc.format.extentxiv, 126 pageseng
dc.identifier.oclc872569215eng
dc.identifier.urihttps://hdl.handle.net/10355/33117
dc.identifier.urihttps://doi.org/10.32469/10355/33117eng
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcollectionUniversity of Missouri--Columbia. Graduate School. Theses and Dissertations.eng
dc.subjectspeech enhancementeng
dc.subjectnoise reductioneng
dc.subjectspectral subtraction methodeng
dc.titleModulation domain processing and speech phase spectrum in speech enhancementeng
dc.typeThesiseng
thesis.degree.disciplineComputer science (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


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