{"id":"https://openalex.org/W4280609203","doi":"https://doi.org/10.1109/taslp.2022.3172631","title":"Generalized Fast Multichannel Nonnegative Matrix Factorization Based on Gaussian Scale Mixtures for Blind Source Separation","display_name":"Generalized Fast Multichannel Nonnegative Matrix Factorization Based on Gaussian Scale Mixtures for Blind Source Separation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4280609203","doi":"https://doi.org/10.1109/taslp.2022.3172631"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2022.3172631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2022.3172631","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2205.05330","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5082784886","display_name":"Mathieu Fontaine","orcid":"https://orcid.org/0000-0002-7657-6271"},"institutions":[{"id":"https://openalex.org/I2802330208","display_name":"Statistics Belgium","ror":"https://ror.org/0246a9012","country_code":"BE","type":"government","lineage":["https://openalex.org/I2802330208","https://openalex.org/I4210095879"]},{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]},{"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":["BE","FR","JP"],"is_corresponding":false,"raw_author_name":"Mathieu Fontaine","raw_affiliation_strings":["LTCI, T&#x00E9;l&#x00E9;com Paris, Institut Polytechnique de Paris, Palaiseau, France","RIKEN Center for Advanced Intelligence Project [Tokyo]","Signal, Statistique et Apprentissage"],"raw_orcid":"https://orcid.org/0000-0002-7657-6271","affiliations":[{"raw_affiliation_string":"LTCI, T&#x00E9;l&#x00E9;com Paris, Institut Polytechnique de Paris, Palaiseau, France","institution_ids":["https://openalex.org/I4210165912"]},{"raw_affiliation_string":"RIKEN Center for Advanced Intelligence Project [Tokyo]","institution_ids":["https://openalex.org/I4210126580"]},{"raw_affiliation_string":"Signal, Statistique et Apprentissage","institution_ids":["https://openalex.org/I2802330208"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069659508","display_name":"Kouhei Sekiguchi","orcid":"https://orcid.org/0000-0001-6160-9301"},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kouhei Sekiguchi","raw_affiliation_strings":["Center for Advanced Intelligence Project (AIP), RIKEN, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0001-6160-9301","affiliations":[{"raw_affiliation_string":"Center for Advanced Intelligence Project (AIP), RIKEN, Tokyo, Japan","institution_ids":["https://openalex.org/I4210126580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082272880","display_name":"Aditya Arie Nugraha","orcid":"https://orcid.org/0000-0001-5424-747X"},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Aditya Arie Nugraha","raw_affiliation_strings":["Center for Advanced Intelligence Project (AIP), RIKEN, Tokyo, Japan"],"raw_orcid":"https://orcid.org/0000-0001-5424-747X","affiliations":[{"raw_affiliation_string":"Center for Advanced Intelligence Project (AIP), RIKEN, Tokyo, Japan","institution_ids":["https://openalex.org/I4210126580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007353694","display_name":"Yoshiaki Bando","orcid":"https://orcid.org/0000-0002-3934-0745"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshiaki Bando","raw_affiliation_strings":["National Institute of Advanced Industrial Science and Technology (AIST), Koto, Tokyo, Japan","Artificial Intelligence Research Center [Tokyo]"],"raw_orcid":"https://orcid.org/0000-0002-3934-0745","affiliations":[{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology (AIST), Koto, Tokyo, Japan","institution_ids":["https://openalex.org/I73613424"]},{"raw_affiliation_string":"Artificial Intelligence Research Center [Tokyo]","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067956319","display_name":"Kazuyoshi Yoshii","orcid":"https://orcid.org/0000-0001-8387-8609"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]},{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuyoshi Yoshii","raw_affiliation_strings":["Center for Advanced Intelligence Project (AIP), RIKEN, Tokyo, Japan","Kyoto University"],"raw_orcid":"https://orcid.org/0000-0001-8387-8609","affiliations":[{"raw_affiliation_string":"Center for Advanced Intelligence Project (AIP), RIKEN, Tokyo, Japan","institution_ids":["https://openalex.org/I4210126580"]},{"raw_affiliation_string":"Kyoto University","institution_ids":["https://openalex.org/I22299242"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1298,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.75837152,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"30","issue":null,"first_page":"1734","last_page":"1748"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9897000193595886,"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/gaussian","display_name":"Gaussian","score":0.6626421213150024},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5839502811431885},{"id":"https://openalex.org/keywords/generalized-inverse-gaussian-distribution","display_name":"Generalized inverse Gaussian distribution","score":0.5778411030769348},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.5338075757026672},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.4754205048084259},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.46973997354507446},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.42286187410354614},{"id":"https://openalex.org/keywords/probability-density-function","display_name":"Probability density function","score":0.4225842356681824},{"id":"https://openalex.org/keywords/additive-white-gaussian-noise","display_name":"Additive white Gaussian noise","score":0.4194117784500122},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4167899191379547},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.39987000823020935},{"id":"https://openalex.org/keywords/gaussian-random-field","display_name":"Gaussian random field","score":0.3469560742378235},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.3013301491737366},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2851096987724304},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1943431794643402},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.10325568914413452}],"concepts":[{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6626421213150024},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5839502811431885},{"id":"https://openalex.org/C18912344","wikidata":"https://www.wikidata.org/wiki/Q866810","display_name":"Generalized inverse Gaussian distribution","level":5,"score":0.5778411030769348},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.5338075757026672},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.4754205048084259},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.46973997354507446},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.42286187410354614},{"id":"https://openalex.org/C197055811","wikidata":"https://www.wikidata.org/wiki/Q207522","display_name":"Probability density function","level":2,"score":0.4225842356681824},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.4194117784500122},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4167899191379547},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.39987000823020935},{"id":"https://openalex.org/C51267290","wikidata":"https://www.wikidata.org/wiki/Q5527848","display_name":"Gaussian random field","level":4,"score":0.3469560742378235},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.3013301491737366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2851096987724304},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1943431794643402},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.10325568914413452},{"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/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"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/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":3,"locations":[{"id":"doi:10.1109/taslp.2022.3172631","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2022.3172631","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"},{"id":"pmh:oai:arXiv.org:2205.05330","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.05330","pdf_url":"https://arxiv.org/pdf/2205.05330","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:HAL:hal-03657196v1","is_oa":false,"landing_page_url":"https://telecom-paris.hal.science/hal-03657196","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE/ACM Transactions on Audio, Speech and Language Processing, 2022, pp.1-1. &#x27E8;10.1109/TASLP.2022.3172631&#x27E9;","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2205.05330","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2205.05330","pdf_url":"https://arxiv.org/pdf/2205.05330","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3489341541","display_name":"Audio-Visual Music Understanding Based on Integration of Recognition and Generative Processes","funder_award_id":"19H04137","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G6575691015","display_name":"A Unified Computational Model for Audio-Visual Recognition of Human Social Interaction","funder_award_id":"20K19833","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W27722686","https://openalex.org/W45374770","https://openalex.org/W58461959","https://openalex.org/W231930959","https://openalex.org/W1490883981","https://openalex.org/W1533511347","https://openalex.org/W1755019093","https://openalex.org/W1857789879","https://openalex.org/W1930734808","https://openalex.org/W1965555277","https://openalex.org/W1975419935","https://openalex.org/W1977691943","https://openalex.org/W1989314204","https://openalex.org/W2003279758","https://openalex.org/W2004152321","https://openalex.org/W2037248439","https://openalex.org/W2072548008","https://openalex.org/W2090418688","https://openalex.org/W2099727712","https://openalex.org/W2108214672","https://openalex.org/W2113990625","https://openalex.org/W2127851351","https://openalex.org/W2143027228","https://openalex.org/W2157588673","https://openalex.org/W2157614506","https://openalex.org/W2168273590","https://openalex.org/W2314640094","https://openalex.org/W2412956798","https://openalex.org/W2536879837","https://openalex.org/W2580692915","https://openalex.org/W2621770314","https://openalex.org/W2792400747","https://openalex.org/W2804891234","https://openalex.org/W2804917410","https://openalex.org/W2805600705","https://openalex.org/W2892163332","https://openalex.org/W2900893004","https://openalex.org/W2902990440","https://openalex.org/W2911579794","https://openalex.org/W2913908511","https://openalex.org/W2918296821","https://openalex.org/W2964080410","https://openalex.org/W2985708164","https://openalex.org/W2997688633","https://openalex.org/W2998251729","https://openalex.org/W3005347330","https://openalex.org/W3081267827","https://openalex.org/W3094989652","https://openalex.org/W3106955634","https://openalex.org/W3114290270","https://openalex.org/W3122509840","https://openalex.org/W3147919432","https://openalex.org/W3161538827","https://openalex.org/W3197709756","https://openalex.org/W3214524466","https://openalex.org/W4292403327","https://openalex.org/W6609044897","https://openalex.org/W6610566761","https://openalex.org/W6682678314","https://openalex.org/W6790964976","https://openalex.org/W7056831425"],"related_works":["https://openalex.org/W2351387116","https://openalex.org/W2361100278","https://openalex.org/W1658347130","https://openalex.org/W2398836525","https://openalex.org/W2178986460","https://openalex.org/W2783340419","https://openalex.org/W2092366338","https://openalex.org/W173472343","https://openalex.org/W2333316694","https://openalex.org/W4248260284"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"heavy-tailed":[3,48,79,135],"extensions":[4,137,183],"of":[5,24,29,78,93,123,140,194],"a":[6,21,75,82,91,144],"state-of-the-art":[7,181],"versatile":[8],"blind":[9],"source":[10],"separation":[11,191],"method":[12],"called":[13,81,104],"fast":[14],"multichannel":[15],"nonnegative":[16],"matrix":[17],"factorization":[18],"(FastMNMF)":[19],"from":[20],"unified":[22],"point":[23],"view.":[25],"The":[26],"common":[27],"way":[28],"deriving":[30],"such":[31],"an":[32,112],"extension":[33],"is":[34],"to":[35],"replace":[36],"the":[37,43,54,69,119,124,149,155,168,175,180,195],"multivariate":[38,55],"complex":[39,56],"Gaussian":[40,65,83,94,165,177],"distribution":[41,152],"in":[42,187,192],"likelihood":[44],"function":[45,122],"with":[46],"its":[47],"generalization,":[49],"<italic":[50,87],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[51,59,88,160],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">e.g.</i>":[52],",":[53,90,163],"Student\u2019s":[57,158],"<inline-formula":[58,159],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[60,161],"notation=\"LaTeX\">$t$</tex-math></inline-formula>":[61,162],"and":[62,67,110,142,164,184,190],"leptokurtic":[63],"generalized":[64,150],"distributions,":[66],"tailor-make":[68],"corresponding":[70],"parameter":[71],"optimization":[72],"algorithm.":[73],"Using":[74],"wider":[76],"class":[77],"distributions":[80,95,166],"scale":[84],"mixture":[85,92],"(GSM),":[86],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">i.e.</i>":[89],"whose":[96],"variances":[97],"are":[98,138],"perturbed":[99],"by":[100],"positive":[101],"random":[102],"scalars":[103],"impulse":[105,125],"variables,":[106],"we":[107],"propose":[108],"GSM-FastMNMF":[109,141],"develop":[111],"expectation-maximization":[113],"algorithm":[114],"that":[115,133,153,174],"works":[116],"even":[117],"when":[118],"probability":[120],"density":[121],"variables":[126],"have":[127],"no":[128],"analytical":[129],"expressions.":[130],"We":[131],"show":[132,173],"existing":[134],"FastMNMF":[136,178,182],"instances":[139],"derive":[143],"new":[145],"instance":[146],"based":[147],"on":[148],"hyperbolic":[151],"include":[154],"normal-inverse":[156,176],"Gaussian,":[157],"as":[167],"special":[169],"cases.":[170],"Our":[171],"experiments":[172],"outperforms":[179],"ILRMA":[185],"model":[186],"speech":[188],"enhancement":[189],"terms":[193],"signal-to-distortion":[196],"ratio.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-09T07:52:08.696243","created_date":"2025-10-10T00:00:00"}