{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/95277"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/95277","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Phase difference and tensor factorization models for audio source separation","abstract":"Made available in DSpace on 2017-03-01T15:46:01Z (GMT). No. of bitstreams: 2 TRAA-DISSERTATION-2016.pdf: 12461339 bytes, checksum: aeab068ca641be012f3b6c8b1f19d354 (MD5) LICENSE.txt: 4210 bytes, checksum: 63ac2ac06dfd739a5099ea28ac00e136 (MD5) Previous issue date: 2016-10-10","abstract_html":"Made available in DSpace on 2017-03-01T15:46:01Z (GMT). No. of bitstreams: 2 TRAA-DISSERTATION-2016.pdf: 12461339 bytes, checksum: aeab068ca641be012f3b6c8b1f19d354 (MD5) LICENSE.txt: 4210 bytes, checksum: 63ac2ac06dfd739a5099ea28ac00e136 (MD5) Previous issue date: 2016-10-10","abstract_has_math":false,"creators":["Traa, Johannes"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Smaragdis, Paris","Hasegawa-Johnson, Mark","Bresler, Yoram","Stein, Noah"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-03-01T15:46:01Z","date_published":"2017-03-01T15:46:01Z","updated_at":"2026-07-22T22:26:35Z","subjects":["Nonnegative matrix factorization","Nonnegative tensor factorization","Interchannel phase differences","Audio Source Separation"],"languages":["en"],"rights":["Copyright 2016 Johannes Traa"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/95277","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Smaragdis, Paris","Hasegawa-Johnson, Mark","Bresler, Yoram","Stein, Noah"]},{"key":"dc:creator","label":"Author","values":["Traa, Johannes"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2017-03-01T15:46:01Z","2016-10-10","2016-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"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":["Nonnegative matrix factorization","Nonnegative tensor factorization","Interchannel phase differences","Audio Source Separation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2016 Johannes Traa"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/95277"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Made available in DSpace on 2017-03-01T15:46:01Z (GMT). No. of bitstreams: 2 TRAA-DISSERTATION-2016.pdf: 12461339 bytes, checksum: aeab068ca641be012f3b6c8b1f19d354 (MD5) LICENSE.txt: 4210 bytes, checksum: 63ac2ac06dfd739a5099ea28ac00e136 (MD5) Previous issue date: 2016-10-10","Audio source separation is a well-known problem in the speech community. Many methods have been proposed to isolate speech signals from a multichannel mixture. In this thesis, we will explore a number of techniques involving interchannel phase difference (IPD) features within a tensor factorization framework. IPD features can be extracted on a time-frequency (TF) grid and are a function of the phase characteristics of the mixing process. Thus, the ultimate goal is to form a clustering of these features and produce TF masks that can be used to perform the separation. We discuss various non-tensor-based methods that are capable of modeling linear and nonlinear IPD trends. Then, we discuss generalizations to both nonnegative and complex tensor factorizations (NTF, CTF). We show that each method performs best in certain circumstances and we conclude by saying that more work is needed to devise a generally superior approach.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-02-28 without embargo terms","The student, Johannes Traa, accepted the attached license on 2016-09-03 at 08:59.","The student, Johannes Traa, submitted this Dissertation for approval on 2016-09-03 at 09:12.","This Dissertation was approved for publication on 2016-10-10 at 08:47.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10144 on 2017-02-28 at 14:45:53"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Phase difference and tensor factorization models for audio source separation"]}]}],"canonical_facts":{"dc:contributor":["Smaragdis, Paris","Hasegawa-Johnson, Mark","Bresler, Yoram","Stein, Noah"],"dc:creator":["Traa, Johannes"],"dc:date":["2017-03-01T15:46:01Z","2016-10-10","2016-12"],"dc:description":["Made available in DSpace on 2017-03-01T15:46:01Z (GMT). No. of bitstreams: 2 TRAA-DISSERTATION-2016.pdf: 12461339 bytes, checksum: aeab068ca641be012f3b6c8b1f19d354 (MD5) LICENSE.txt: 4210 bytes, checksum: 63ac2ac06dfd739a5099ea28ac00e136 (MD5) Previous issue date: 2016-10-10","Audio source separation is a well-known problem in the speech community. Many methods have been proposed to isolate speech signals from a multichannel mixture. In this thesis, we will explore a number of techniques involving interchannel phase difference (IPD) features within a tensor factorization framework. IPD features can be extracted on a time-frequency (TF) grid and are a function of the phase characteristics of the mixing process. Thus, the ultimate goal is to form a clustering of these features and produce TF masks that can be used to perform the separation. We discuss various non-tensor-based methods that are capable of modeling linear and nonlinear IPD trends. Then, we discuss generalizations to both nonnegative and complex tensor factorizations (NTF, CTF). We show that each method performs best in certain circumstances and we conclude by saying that more work is needed to devise a generally superior approach.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-02-28 without embargo terms","The student, Johannes Traa, accepted the attached license on 2016-09-03 at 08:59.","The student, Johannes Traa, submitted this Dissertation for approval on 2016-09-03 at 09:12.","This Dissertation was approved for publication on 2016-10-10 at 08:47.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10144 on 2017-02-28 at 14:45:53"],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/2142/95277"],"dc:language":["en"],"dc:rights":["Copyright 2016 Johannes Traa"],"dc:subject":["Nonnegative matrix factorization","Nonnegative tensor factorization","Interchannel phase differences","Audio Source Separation"],"dc:title":["Phase difference and tensor factorization models for audio source separation"],"dc:type":["text"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:35Z"}