{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/46649"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/46649","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Kurtosis-based blind beamforming: an adaptive, subband implementation with a convergence improvement","abstract":"In many speech applications, a single talker is captured in the presence of background noise using a multi-microphone array. Without knowledge of the array geometry, talker location, or the room response, many traditional beamforming techniques cannot be used effectively. An adaptive, maximum-kurtosis objective is used in the frequency domain to blindly enhance the speech signal. The algorithm provides SNR gains of 3.5 - 7.5 dB with just two microphones in low-SNR, real-world scenarios. An improvement is presented that allows for faster and more stable convergence of the algorithm in real-time implementations. Finally, an alternative formulation to the problem is given, framing it in a way that might inspire new discussion or alternative solutions.","abstract_html":"In many speech applications, a single talker is captured in the presence of background noise using a multi-microphone array. Without knowledge of the array geometry, talker location, or the room response, many traditional beamforming techniques cannot be used effectively. An adaptive, maximum-kurtosis objective is used in the frequency domain to blindly enhance the speech signal. The algorithm provides SNR gains of 3.5 - 7.5 dB with just two microphones in low-SNR, real-world scenarios. An improvement is presented that allows for faster and more stable convergence of the algorithm in real-time implementations. Finally, an alternative formulation to the problem is given, framing it in a way that might inspire new discussion or alternative solutions.","abstract_has_math":false,"creators":["Klingler, Daniel"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":["Jones, Douglas L."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-01-16T17:57:30Z","date_published":"2014-01-16T17:57:30Z","updated_at":"2026-07-22T22:25:36Z","subjects":["Speech Enhancement","Maximum Kurtosis","Subband Implementation","Convergence Improvement","Beamforming","Noise Reduction"],"languages":["en"],"rights":["Copyright 2013 Daniel Klingler"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/46649","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Jones, Douglas L."]},{"key":"dc:creator","label":"Author","values":["Klingler, Daniel"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-01-16T17:57:30Z","2013-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Speech Enhancement","Maximum Kurtosis","Subband Implementation","Convergence Improvement","Beamforming","Noise Reduction"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2013 Daniel Klingler"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/46649"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["In many speech applications, a single talker is captured in the presence of background noise using a multi-microphone array. 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