{"id":"https://openalex.org/W2113990625","doi":"https://doi.org/10.1109/tasl.2009.2031510","title":"Multichannel Nonnegative Matrix Factorization in Convolutive Mixtures for Audio Source Separation","display_name":"Multichannel Nonnegative Matrix Factorization in Convolutive Mixtures for Audio Source Separation","publication_year":2009,"publication_date":"2009-09-04","ids":{"openalex":"https://openalex.org/W2113990625","doi":"https://doi.org/10.1109/tasl.2009.2031510","mag":"2113990625"},"language":"en","primary_location":{"id":"doi:10.1109/tasl.2009.2031510","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2009.2031510","pdf_url":null,"source":{"id":"https://openalex.org/S199497470","display_name":"IEEE Transactions on Audio Speech and Language Processing","issn_l":"1558-7916","issn":["1558-7916","1558-7924"],"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 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/A5073788938","display_name":"Alexey Ozerov","orcid":"https://orcid.org/0000-0003-4834-5166"},"institutions":[{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I205703379","display_name":"Institut Mines-T\u00e9l\u00e9com","ror":"https://ror.org/025vp2923","country_code":"FR","type":"facility","lineage":["https://openalex.org/I205703379"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"A. Ozerov","raw_affiliation_strings":["Institut Telecom,CNRS LTCI, TELECOM ParisTech, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Telecom,CNRS LTCI, TELECOM ParisTech, Paris, France","institution_ids":["https://openalex.org/I12356871","https://openalex.org/I1294671590","https://openalex.org/I205703379","https://openalex.org/I4210165912"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022368934","display_name":"C\u00e9dric F\u00e9votte","orcid":"https://orcid.org/0000-0003-3801-5534"},"institutions":[{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210165912","display_name":"Laboratoire Traitement et Communication de l\u2019Information","ror":"https://ror.org/057er4c39","country_code":"FR","type":"facility","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102","https://openalex.org/I4210165912"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"C. Fevotte","raw_affiliation_strings":["CNRS LTCI, TELECOM ParisTech, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CNRS LTCI, TELECOM ParisTech, Paris, France","institution_ids":["https://openalex.org/I12356871","https://openalex.org/I1294671590","https://openalex.org/I4210165912"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":27.0088,"has_fulltext":false,"cited_by_count":608,"citation_normalized_percentile":{"value":0.99861111,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"18","issue":"3","first_page":"550","last_page":"563"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":1.0,"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":1.0,"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":0.9998000264167786,"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":0.9969000220298767,"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/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.8825176954269409},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.7694101929664612},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.6634783744812012},{"id":"https://openalex.org/keywords/underdetermined-system","display_name":"Underdetermined system","score":0.5791565775871277},{"id":"https://openalex.org/keywords/short-time-fourier-transform","display_name":"Short-time Fourier transform","score":0.5411838889122009},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5392732620239258},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5347496867179871},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49309584498405457},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4608139395713806},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.45687663555145264},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44804537296295166},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.4434005916118622},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.4359127879142761},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4139573574066162},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39031651616096497},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3699679374694824},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.1496099829673767},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14379891753196716},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1082058846950531},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.09904319047927856}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.8825176954269409},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.7694101929664612},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.6634783744812012},{"id":"https://openalex.org/C179690561","wikidata":"https://www.wikidata.org/wiki/Q4316110","display_name":"Underdetermined system","level":2,"score":0.5791565775871277},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.5411838889122009},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5392732620239258},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5347496867179871},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49309584498405457},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4608139395713806},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.45687663555145264},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44804537296295166},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.4434005916118622},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.4359127879142761},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4139573574066162},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39031651616096497},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3699679374694824},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.1496099829673767},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14379891753196716},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1082058846950531},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.09904319047927856},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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/tasl.2009.2031510","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2009.2031510","pdf_url":null,"source":{"id":"https://openalex.org/S199497470","display_name":"IEEE Transactions on Audio Speech and Language Processing","issn_l":"1558-7916","issn":["1558-7916","1558-7924"],"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 Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.47999998927116394}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W55044442","https://openalex.org/W64505202","https://openalex.org/W165956390","https://openalex.org/W176887922","https://openalex.org/W250076511","https://openalex.org/W1500379785","https://openalex.org/W1504438288","https://openalex.org/W1510097680","https://openalex.org/W1547060653","https://openalex.org/W1555631305","https://openalex.org/W1564244060","https://openalex.org/W1606647324","https://openalex.org/W1752780498","https://openalex.org/W1780344239","https://openalex.org/W1851993003","https://openalex.org/W1876052200","https://openalex.org/W1902027874","https://openalex.org/W1965392255","https://openalex.org/W1965586400","https://openalex.org/W2018457194","https://openalex.org/W2039844283","https://openalex.org/W2048687561","https://openalex.org/W2049633694","https://openalex.org/W2073502026","https://openalex.org/W2082542187","https://openalex.org/W2098723113","https://openalex.org/W2098918476","https://openalex.org/W2099904336","https://openalex.org/W2100335648","https://openalex.org/W2101303708","https://openalex.org/W2104298926","https://openalex.org/W2117042571","https://openalex.org/W2117853077","https://openalex.org/W2119741678","https://openalex.org/W2124149378","https://openalex.org/W2124195644","https://openalex.org/W2128911505","https://openalex.org/W2137969290","https://openalex.org/W2138842265","https://openalex.org/W2139302694","https://openalex.org/W2144039164","https://openalex.org/W2144920235","https://openalex.org/W2145668323","https://openalex.org/W2150415460","https://openalex.org/W2156889498","https://openalex.org/W2167546860","https://openalex.org/W2950250097","https://openalex.org/W6602628551","https://openalex.org/W6607207477","https://openalex.org/W6637795923","https://openalex.org/W6637837750","https://openalex.org/W6638971552","https://openalex.org/W6654907530","https://openalex.org/W6674864272","https://openalex.org/W6930559537"],"related_works":["https://openalex.org/W2361100278","https://openalex.org/W2352539002","https://openalex.org/W2547262076","https://openalex.org/W2563421448","https://openalex.org/W1565566036","https://openalex.org/W2594498979","https://openalex.org/W2774154397","https://openalex.org/W2982840733","https://openalex.org/W2534043196","https://openalex.org/W2806198829"],"abstract_inverted_index":{"We":[0,24,72],"consider":[1],"inference":[2],"in":[3,26,42,136],"a":[4,16,51,65,118],"general":[5],"data-driven":[6],"object-based":[7],"model":[8,52,67],"of":[9,21,68,75,88,94,107,111,114],"multichannel":[10,96],"audio":[11,133],"data,":[12],"assumed":[13],"generated":[14],"as":[15,38,153,155,170],"possibly":[17],"underdetermined":[18],"convolutive":[19,151],"mixture":[20],"source":[22,47,79,134],"signals.":[23],"work":[25],"the":[27,60,76,90,95,109,176],"short-time":[28],"Fourier":[29],"transform":[30],"(STFT)":[31],"domain,":[32],"where":[33],"convolution":[34],"is":[35,49],"routinely":[36],"approximated":[37],"linear":[39],"instantaneous":[40,149],"mixing":[41,77],"each":[43],"frequency":[44],"band.":[45],"Each":[46],"STFT":[48],"given":[50],"inspired":[53,122],"from":[54,123,175],"nonnegative":[55],"matrix":[56],"factorization":[57],"(NMF)":[58],"with":[59,166],"Itakura-Saito":[61],"divergence,":[62],"which":[63],"underlies":[64],"statistical":[66],"superimposed":[69],"Gaussian":[70],"components.":[71],"address":[73],"estimation":[74],"and":[78,141,145,150],"parameters":[80],"using":[81,98,117],"two":[82,173],"methods.":[83],"The":[84,103],"first":[85],"one":[86],"consists":[87,106],"maximizing":[89,108],"exact":[91],"joint":[92],"likelihood":[93],"data":[97],"an":[99],"expectation-maximization":[100],"(EM)":[101],"algorithm.":[102],"second":[104],"method":[105,162],"sum":[110],"individual":[112],"likelihoods":[113],"all":[115],"channels":[116],"multiplicative":[119],"update":[120],"algorithm":[121],"NMF":[124],"methodology.":[125],"Our":[126,160],"decomposition":[127],"algorithms":[128],"are":[129],"applied":[130],"to":[131,168],"stereo":[132],"separation":[135],"various":[137],"settings,":[138],"covering":[139],"blind":[140],"supervised":[142],"separation,":[143],"music":[144,158],"speech":[146],"sources,":[147],"synthetic":[148],"mixtures,":[152],"well":[154],"professionally":[156],"produced":[157],"recordings.":[159],"EM":[161],"produces":[163],"competitive":[164],"results":[165],"respect":[167],"state-of-the-art":[169],"illustrated":[171],"on":[172],"tasks":[174],"international":[177],"Signal":[178],"Separation":[179],"Evaluation":[180],"Campaign":[181],"(SiSEC":[182],"2008).":[183]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":27},{"year":2021,"cited_by_count":47},{"year":2020,"cited_by_count":41},{"year":2019,"cited_by_count":73},{"year":2018,"cited_by_count":66},{"year":2017,"cited_by_count":67},{"year":2016,"cited_by_count":38},{"year":2015,"cited_by_count":41},{"year":2014,"cited_by_count":36},{"year":2013,"cited_by_count":20},{"year":2012,"cited_by_count":31}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}
