{"id":"https://openalex.org/W4386536172","doi":"https://doi.org/10.1109/taslp.2023.3313446","title":"Multi-Frame Full-Rank Spatial Covariance Analysis for Underdetermined Blind Source Separation and Dereverberation","display_name":"Multi-Frame Full-Rank Spatial Covariance Analysis for Underdetermined Blind Source Separation and Dereverberation","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386536172","doi":"https://doi.org/10.1109/taslp.2023.3313446"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2023.3313446","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2023.3313446","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007032557","display_name":"Hiroshi Sawada","orcid":"https://orcid.org/0000-0002-4831-9286"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Sawada","raw_affiliation_strings":["NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0002-4831-9286","affiliations":[{"raw_affiliation_string":"NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084590882","display_name":"Rintaro Ikeshita","orcid":"https://orcid.org/0000-0003-2608-1999"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Rintaro Ikeshita","raw_affiliation_strings":["NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0003-2608-1999","affiliations":[{"raw_affiliation_string":"NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069398831","display_name":"Keisuke Kinoshita","orcid":"https://orcid.org/0009-0008-7987-8188"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]},{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP","US"],"is_corresponding":false,"raw_author_name":"Keisuke Kinoshita","raw_affiliation_strings":["NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation, Kyoto, Japan","Google Inc, USA"],"raw_orcid":"https://orcid.org/0009-0008-7987-8188","affiliations":[{"raw_affiliation_string":"NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"Google Inc, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021240106","display_name":"Tomohiro Nakatani","orcid":"https://orcid.org/0000-0002-7487-7150"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomohiro Nakatani","raw_affiliation_strings":["NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0002-7487-7150","affiliations":[{"raw_affiliation_string":"NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5657,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.84255866,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"31","issue":null,"first_page":"3589","last_page":"3602"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.972000002861023,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.690181314945221},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6381361484527588},{"id":"https://openalex.org/keywords/underdetermined-system","display_name":"Underdetermined system","score":0.5742495059967041},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5625463724136353},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5494061708450317},{"id":"https://openalex.org/keywords/canonical-correlation","display_name":"Canonical correlation","score":0.48358315229415894},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4748972952365875},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.4695870280265808},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46847811341285706},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.46241021156311035},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.45116284489631653},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4386111795902252},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.42419975996017456},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.360576331615448},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27504265308380127},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1912354826927185},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.14112240076065063}],"concepts":[{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.690181314945221},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6381361484527588},{"id":"https://openalex.org/C179690561","wikidata":"https://www.wikidata.org/wiki/Q4316110","display_name":"Underdetermined system","level":2,"score":0.5742495059967041},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5625463724136353},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5494061708450317},{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.48358315229415894},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4748972952365875},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.4695870280265808},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46847811341285706},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.46241021156311035},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.45116284489631653},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4386111795902252},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.42419975996017456},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.360576331615448},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27504265308380127},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1912354826927185},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.14112240076065063},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taslp.2023.3313446","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2023.3313446","pdf_url":null,"source":{"id":"https://openalex.org/S4210169297","display_name":"IEEE/ACM Transactions on Audio Speech and Language Processing","issn_l":"2329-9290","issn":["2329-9290","2329-9304"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W184454132","https://openalex.org/W285277413","https://openalex.org/W1486890919","https://openalex.org/W1489793438","https://openalex.org/W1543386260","https://openalex.org/W1601795611","https://openalex.org/W1981755271","https://openalex.org/W1983812858","https://openalex.org/W1996355918","https://openalex.org/W2002146237","https://openalex.org/W2003203076","https://openalex.org/W2014768838","https://openalex.org/W2027884847","https://openalex.org/W2031583051","https://openalex.org/W2046233597","https://openalex.org/W2049633694","https://openalex.org/W2050551142","https://openalex.org/W2093258380","https://openalex.org/W2096819401","https://openalex.org/W2096855653","https://openalex.org/W2097584344","https://openalex.org/W2099741732","https://openalex.org/W2108384452","https://openalex.org/W2109987668","https://openalex.org/W2113139249","https://openalex.org/W2117332620","https://openalex.org/W2143027228","https://openalex.org/W2156676906","https://openalex.org/W2159071216","https://openalex.org/W2164502538","https://openalex.org/W2167398706","https://openalex.org/W2168273590","https://openalex.org/W2170768669","https://openalex.org/W2412956798","https://openalex.org/W2552290276","https://openalex.org/W2788288387","https://openalex.org/W2796809853","https://openalex.org/W2918296821","https://openalex.org/W2946521785","https://openalex.org/W2981096075","https://openalex.org/W2984752454","https://openalex.org/W3016114588","https://openalex.org/W3100336094","https://openalex.org/W3115585868","https://openalex.org/W3127348940","https://openalex.org/W3151596526","https://openalex.org/W3161538827","https://openalex.org/W3163542373","https://openalex.org/W4205778870","https://openalex.org/W4210408276","https://openalex.org/W4225326943","https://openalex.org/W4285203473","https://openalex.org/W4296927107","https://openalex.org/W4385823318","https://openalex.org/W6629071765","https://openalex.org/W6769307377"],"related_works":["https://openalex.org/W2390344110","https://openalex.org/W2364896863","https://openalex.org/W2095924515","https://openalex.org/W2361066326","https://openalex.org/W2383973401","https://openalex.org/W2046761971","https://openalex.org/W2182042810","https://openalex.org/W2351680970","https://openalex.org/W2030887432","https://openalex.org/W2034312940"],"abstract_inverted_index":{"Full-rank":[0],"spatial":[1],"covariance":[2],"analysis":[3],"(FCA)":[4],"is":[5],"a":[6],"technique":[7],"for":[8],"blind":[9,159],"source":[10,74,118],"separation":[11],"(BSS),":[12],"and":[13,154,158],"can":[14],"be":[15],"applied":[16],"to":[17,36,55,114,130],"underdetermined":[18],"situations":[19],"where":[20],"the":[21,24,38,42,57,61,77,84,109,117,132,139,147],"sources":[22],"outnumber":[23],"microphones.":[25],"This":[26],"paper":[27],"proposes":[28],"multi-frame":[29,141],"FCA":[30,35,69,79,111,142,149],"as":[31],"an":[32,68,126],"extension":[33,96],"of":[34,60,105],"improve":[37],"BSS":[39,152,157],"performance":[40],"when":[41],"room":[43],"reverberations":[44],"are":[45,53],"not":[46,82],"so":[47],"short":[48],"that":[49,71,138],"multiple":[50,98,121],"time":[51,88,99,122],"frames":[52,89,100],"needed":[54],"cover":[56],"dominant":[58],"parts":[59],"reverberations.":[62],"There":[63],"has":[64],"already":[65],"been":[66],"proposed":[67,140],"model":[70,80,116,133],"considers":[72],"delayed":[73],"components.":[75],"However,":[76],"existing":[78,110,148],"does":[81],"take":[83],"correlation":[85],"between":[86],"different":[87],"into":[90],"account.":[91],"In":[92],"contrast,":[93],"our":[94],"new":[95],"models":[97],"with":[101],"multivariate":[102],"Gaussian":[103],"distributions":[104],"larger":[106],"dimensionality":[107],"than":[108,146],"models,":[112],"aiming":[113],"better":[115,145],"components":[119],"spanning":[120],"frames.":[123],"We":[124],"derive":[125],"expectation-maximization":[127],"(EM)":[128],"algorithm":[129],"optimize":[131],"parameters.":[134],"Experimental":[135],"results":[136],"show":[137],"performed":[143],"clearly":[144],"techniques":[150],"in":[151],"tasks":[153],"also":[155],"joint":[156],"dereverberation":[160],"tasks.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
