{"id":"https://openalex.org/W2922363796","doi":"https://doi.org/10.1109/taslp.2019.2903288","title":"Dirichlet Latent Variable Model: A Dynamic Model Based on Dirichlet Prior for Audio Processing","display_name":"Dirichlet Latent Variable Model: A Dynamic Model Based on Dirichlet Prior for Audio Processing","publication_year":2019,"publication_date":"2019-03-06","ids":{"openalex":"https://openalex.org/W2922363796","doi":"https://doi.org/10.1109/taslp.2019.2903288","mag":"2922363796"},"language":"en","primary_location":{"id":"doi:10.1109/taslp.2019.2903288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2019.2903288","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/A5072023197","display_name":"Anurendra Kumar","orcid":"https://orcid.org/0000-0002-8052-1492"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Anurendra Kumar","raw_affiliation_strings":["Indian Institute of Technology Delhi, New Delhi, Delhi, IN"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Delhi, New Delhi, Delhi, IN","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021354054","display_name":"Tanaya Guha","orcid":"https://orcid.org/0000-0003-2167-4891"},"institutions":[{"id":"https://openalex.org/I39555362","display_name":"University of Warwick","ror":"https://ror.org/01a77tt86","country_code":"GB","type":"education","lineage":["https://openalex.org/I39555362"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tanaya Guha","raw_affiliation_strings":["University of Warwick, Coventry, West Midlands, GB"],"affiliations":[{"raw_affiliation_string":"University of Warwick, Coventry, West Midlands, GB","institution_ids":["https://openalex.org/I39555362"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101685661","display_name":"Prasanta Kumar Ghosh","orcid":"https://orcid.org/0000-0002-1137-0838"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Prasanta Kumar Ghosh","raw_affiliation_strings":["Indian Institute of Science, Bangalore, Karnataka, IN"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Science, Bangalore, Karnataka, IN","institution_ids":["https://openalex.org/I59270414"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5072023197"],"corresponding_institution_ids":["https://openalex.org/I68891433"],"apc_list":null,"apc_paid":null,"fwci":0.167,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.41481527,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"27","issue":"5","first_page":"919","last_page":"931"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T11309","display_name":"Music and Audio Processing","score":0.9990000128746033,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.8317001461982727},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.7492327690124512},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6694794297218323},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.6356973648071289},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.49240052700042725},{"id":"https://openalex.org/keywords/latent-variable-model","display_name":"Latent variable model","score":0.4845813512802124},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4725223183631897},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.4213446378707886},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.41534969210624695},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39857012033462524},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36887627840042114},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2410784363746643},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.22502008080482483},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.10167571902275085},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09722498059272766}],"concepts":[{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.8317001461982727},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.7492327690124512},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6694794297218323},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.6356973648071289},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.49240052700042725},{"id":"https://openalex.org/C65965080","wikidata":"https://www.wikidata.org/wiki/Q1806885","display_name":"Latent variable model","level":3,"score":0.4845813512802124},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4725223183631897},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.4213446378707886},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.41534969210624695},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39857012033462524},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36887627840042114},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2410784363746643},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.22502008080482483},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.10167571902275085},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09722498059272766},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/taslp.2019.2903288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taslp.2019.2903288","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:eprints.iisc.ac.in:62534","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196309","display_name":"NOT FOUND REPOSITORY (Indian Institute of Science Bangalore)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59270414","host_organization_name":"Indian Institute of Science Bangalore","host_organization_lineage":["https://openalex.org/I59270414"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},{"id":"pmh:oai:wrap.warwick.ac.uk:119932","is_oa":false,"landing_page_url":"http://wrap.warwick.ac.uk/119932/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400665","display_name":"Warwick Research Archive Portal (University of Warwick)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39555362","host_organization_name":"University of Warwick","host_organization_lineage":["https://openalex.org/I39555362"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","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":43,"referenced_works":["https://openalex.org/W584423923","https://openalex.org/W1574263887","https://openalex.org/W1880262756","https://openalex.org/W1902027874","https://openalex.org/W1968154520","https://openalex.org/W1974774036","https://openalex.org/W1981564949","https://openalex.org/W1984213819","https://openalex.org/W1986227484","https://openalex.org/W2000911789","https://openalex.org/W2008198300","https://openalex.org/W2010273021","https://openalex.org/W2013002270","https://openalex.org/W2013608223","https://openalex.org/W2026065824","https://openalex.org/W2039844283","https://openalex.org/W2098571827","https://openalex.org/W2103189252","https://openalex.org/W2103450980","https://openalex.org/W2104266187","https://openalex.org/W2118718620","https://openalex.org/W2124149378","https://openalex.org/W2127851351","https://openalex.org/W2131752723","https://openalex.org/W2135151673","https://openalex.org/W2143959252","https://openalex.org/W2145012779","https://openalex.org/W2150415460","https://openalex.org/W2158216966","https://openalex.org/W2160697975","https://openalex.org/W2162514423","https://openalex.org/W2165530388","https://openalex.org/W2206458544","https://openalex.org/W2283599234","https://openalex.org/W2487466091","https://openalex.org/W2800235295","https://openalex.org/W4233135949","https://openalex.org/W4233759611","https://openalex.org/W4253803149","https://openalex.org/W6634388854","https://openalex.org/W6639619044","https://openalex.org/W6677759377","https://openalex.org/W6679714990"],"related_works":["https://openalex.org/W2769501189","https://openalex.org/W4315588616","https://openalex.org/W4312773271","https://openalex.org/W2888805565","https://openalex.org/W2962686197","https://openalex.org/W2207653751","https://openalex.org/W3005513013","https://openalex.org/W2611137333","https://openalex.org/W4291700620","https://openalex.org/W4317422773"],"abstract_inverted_index":{"We":[0,16,61,74,119],"propose":[1],"a":[2,18,30,87,125,138,163],"dynamic":[3,31,37,139],"latent":[4,9,70,106,110],"variable":[5,71],"model":[6,66,72,183],"for":[7,80,149,166],"learning":[8,108],"bases":[10],"from":[11],"time":[12],"varying,":[13],"non-negative":[14,115],"data.":[15],"take":[17],"probabilistic":[19],"approach":[20],"to":[21,44,63,103],"modeling":[22],"the":[23,64,68,81,95,100,181],"temporal":[24],"dependence":[25],"in":[26,57,189],"data":[27],"by":[28],"introducing":[29],"Dirichlet":[32,34,59,69],"prior\u2014a":[33],"distribution":[35,41],"with":[36],"parameters.":[38,96],"This":[39],"new":[40,164],"allows":[42],"us":[43],"assure":[45],"non-negativity":[46],"and":[47,84,114,131,157],"avoid":[48],"intractability":[49],"when":[50],"sequential":[51],"updates":[52],"are":[53],"performed":[54],"(otherwise":[55],"encountered":[56],"using":[58],"prior).":[60],"refer":[62],"proposed":[65,82,101,182],"as":[67,137],"(DLVM).":[73],"develop":[75],"an":[76],"expectation":[77],"maximization":[78],"algorithm":[79,165],"model,":[83],"also":[85,170],"derive":[86],"maximum":[88],"<italic":[89],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[90],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">a":[91],"posteriori</i>":[92],"estimate":[93],"of":[94,128,141,145],"Furthermore,":[97],"we":[98,178],"connect":[99],"DLVM":[102,133,146],"two":[104],"popular":[105],"basis":[107],"methods\u2014probabilistic":[109],"component":[111],"analysis":[112],"(PLCA)":[113],"matrix":[116],"factorization":[117],"(NMF).":[118],"show":[120,179],"that":[121,180],"1)":[122],"PLCA":[123],"is":[124,147,169],"special":[126],"case":[127],"our":[129],"DLVM,":[130],"2)":[132],"can":[134],"be":[135],"interpreted":[136],"version":[140],"NMF.":[142],"The":[143],"usefulness":[144],"demonstrated":[148],"three":[150,191],"audio":[151],"processing":[152],"applications\u2014speaker":[153],"source":[154,167],"separation,":[155],"denoising,":[156],"bandwidth":[158],"expansion.":[159],"To":[160],"this":[161],"end,":[162],"separation":[168],"proposed.":[171],"Through":[172],"extensive":[173],"experiments":[174],"on":[175],"benchmark":[176],"databases,":[177],"outperforms":[184],"several":[185],"relevant":[186],"existing":[187],"methods":[188],"all":[190],"applications.":[192]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}