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Thomas F. Quatieri. Wang, Tianyu Tom Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2008-11-07T18:58:24Z 2008-11-07T18:58:24Z 2008 2008 http://hdl.handle.net/1721.1/43067 244108342 Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. Includes bibliographical references (p. 133-135). This thesis addresses the problem of obtaining an accurate spectral representation of speech formant structure when the voicing source exhibits a high fundamental frequency. Our work is inspired by auditory perception and physiological modeling studies implicating the use of temporal changes in speech by humans. Specifically, we develop and evaluate signal processing schemes that exploit temporal change of pitch as a basis for high-pitch formant estimation. As part of our development, we assess the source-filter separation capabilities of several two-dimensional processing schemes that utilize both standard spectrographic and auditory-based time-frequency representations. Our methods show quantitative improvements under certain conditions over representations derived from traditional and homomorphic linear prediction. We conclude by highlighting potential benefits of our framework in the particular application of speaker recognition with preliminary results indicating a performance gender-gap closure on subsets of the TIMIT corpus. by Tianyu Tom Wang. S.M. 135 p. eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Exploiting pitch dynamics for speech spectral estimation using a two-dimensional processing framework Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="caca62d6-1642-4111-a731-4f5937d2f418"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Exploiting pitch dynamics for speech spectral estimation using a two-dimensional processing framework</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2008</PublicationDate> <Authors> <Author> <DisplayName>Wang, Tianyu Tom</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>This thesis addresses the problem of obtaining an accurate spectral representation of speech formant structure when the voicing source exhibits a high fundamental frequency. Our work is inspired by auditory perception and physiological modeling studies implicating the use of temporal changes in speech by humans. Specifically, we develop and evaluate signal processing schemes that exploit temporal change of pitch as a basis for high-pitch formant estimation. As part of our development, we assess the source-filter separation capabilities of several two-dimensional processing schemes that utilize both standard spectrographic and auditory-based time-frequency representations. Our methods show quantitative improvements under certain conditions over representations derived from traditional and homomorphic linear prediction. We conclude by highlighting potential benefits of our framework in the particular application of speaker recognition with preliminary results indicating a performance gender-gap closure on subsets of the TIMIT corpus.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>