{"id":158065,"date":"2001-05-01T00:00:00","date_gmt":"2001-05-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/speech-dereverberation-via-maximum-kurtosis-subband-adaptive-filtering\/"},"modified":"2018-10-16T20:10:18","modified_gmt":"2018-10-17T03:10:18","slug":"speech-dereverberation-via-maximum-kurtosis-subband-adaptive-filtering","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/speech-dereverberation-via-maximum-kurtosis-subband-adaptive-filtering\/","title":{"rendered":"Speech Dereverberation via Maximum-Kurtosis Subband Adaptive Filtering"},"content":{"rendered":"<div class=\"asset-content\">\n<p>This paper presents an efficient algorithm for high-quality speech capture in applications such as hands-free teleconferencing or voice recording by personal computers. We process the microphone signals by a subband adaptive filtering structure using a modulated complex lapped transform (MCLT), in which the subband filters are adapted to maximize the kurtosis of the linear prediction (LP) residual of the reconstructed speech. In this way, we attain good solutions to the problem of blind speech dereverberation. Experimental results with actual data, as well as with artificially difficult reverberant situations, show very good per-formance, both in terms of a significant reduction of the perceived reverberation, as well as improvement in spectral fidelity.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper presents an efficient algorithm for high-quality speech capture in applications such as hands-free teleconferencing or voice recording by personal computers. We process the microphone signals by a subband adaptive filtering structure using a modulated complex lapped transform (MCLT), in which the subband filters are adapted to maximize the kurtosis of the linear prediction [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"Institute of Electrical and Electronics Engineers, Inc.","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"International Conference on Acoustics, Speech, and Signal Processing","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"\u00a9 2001 IEEE. Personal use of this material is permitted. However, permission to reprint\/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.","msr_conference_name":"International Conference on Acoustics, Speech, and Signal Processing","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"B. W. Gillespie, D. A. F. Florencio, H. S. 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