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Charlotte M. Reed and Louis D. Braida. D'Aquila, Laura A Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2016-12-22T15:19:02Z 2016-12-22T15:19:02Z 2016 2016 http://hdl.handle.net/1721.1/106025 965830699 Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 41-42). The masking release (MR; i.e., better speech recognition in fluctuating compared to continuous noise backgrounds) that is evident for normal-hearing (NH) listeners is generally reduced or absent in hearing-impaired (HI) listeners. In this study, a signal-processing technique was developed to improve MR in HI listeners and offer insight into the mechanisms influencing the size of MR. This technique compares short-term and long-term estimates of energy, increases the level of short-term segments whose energy is below the average energy, and normalizes the overall energy of the processed signal to be equivalent to that of the original long-term estimate. In consonant-identification tests, HI listeners achieved similar scores for processed and unprocessed stimuli in quiet and in continuous-noise backgrounds, while superior performance was obtained for the processed speech in some of the fluctuating background noises. Thus, the energy-normalized signals led to larger values of MR compared to that obtained with unprocessed signals. by Laura A. D'Aquila. M.Eng. 98 pages 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. Improving speech intelligibility in fluctuating background interference Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="9a82da8b-ab43-4c57-b9db-7ece42284b76"> <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>Improving speech intelligibility in fluctuating background interference</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2016</PublicationDate> <Authors> <Author> <DisplayName>D&apos;Aquila, Laura A</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>The masking release (MR; i.e., better speech recognition in fluctuating compared to continuous noise backgrounds) that is evident for normal-hearing (NH) listeners is generally reduced or absent in hearing-impaired (HI) listeners. In this study, a signal-processing technique was developed to improve MR in HI listeners and offer insight into the mechanisms influencing the size of MR. This technique compares short-term and long-term estimates of energy, increases the level of short-term segments whose energy is below the average energy, and normalizes the overall energy of the processed signal to be equivalent to that of the original long-term estimate. In consonant-identification tests, HI listeners achieved similar scores for processed and unprocessed stimuli in quiet and in continuous-noise backgrounds, while superior performance was obtained for the processed speech in some of the fluctuating background noises. Thus, the energy-normalized signals led to larger values of MR compared to that obtained with unprocessed signals.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>