{"id":"https://openalex.org/W2757279226","doi":"https://doi.org/10.1109/waspaa.2017.8170034","title":"Deep recurrent NMF for speech separation by unfolding iterative thresholding","display_name":"Deep recurrent NMF for speech separation by unfolding iterative thresholding","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2757279226","doi":"https://doi.org/10.1109/waspaa.2017.8170034","mag":"2757279226"},"language":"en","primary_location":{"id":"doi:10.1109/waspaa.2017.8170034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/waspaa.2017.8170034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1709.07124","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053447215","display_name":"Scott Wisdom","orcid":"https://orcid.org/0000-0001-6671-1428"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Scott Wisdom","raw_affiliation_strings":["Department of Electrical Engineering, University of Washington, Seattle, WA, USA","Department of Electrical Engineering, University of Washington Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]},{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111815587","display_name":"Thomas A. Powers","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas Powers","raw_affiliation_strings":["Department of Electrical Engineering, University of Washington, Seattle, WA, USA","Department of Electrical Engineering, University of Washington Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]},{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067698354","display_name":"J.W. Pitton","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]},{"id":"https://openalex.org/I4210138199","display_name":"University of Washington Applied Physics Laboratory","ror":"https://ror.org/03d17d270","country_code":"US","type":"facility","lineage":["https://openalex.org/I201448701","https://openalex.org/I4210138199"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Pitton","raw_affiliation_strings":["Applied Physics Laboratory, University of Washington, Seattle, WA, USA","Department of Electrical Engineering, University of Washington Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Applied Physics Laboratory, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I4210138199"]},{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019670377","display_name":"Les Atlas","orcid":"https://orcid.org/0009-0001-9979-5864"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Les Atlas","raw_affiliation_strings":["Department of Electrical Engineering, University of Washington, Seattle, WA, USA","Department of Electrical Engineering, University of Washington Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]},{"raw_affiliation_string":"Department of Electrical Engineering, University of Washington Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5053447215"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12562368,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","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/T10860","display_name":"Speech and Audio Processing","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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.8715336322784424},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7463487982749939},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7332392334938049},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.697270393371582},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6300613880157471},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.4940338730812073},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4861604869365692},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.47018304467201233},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.37597984075546265},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07412412762641907}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.8715336322784424},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7463487982749939},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7332392334938049},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.697270393371582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6300613880157471},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.4940338730812073},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4861604869365692},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.47018304467201233},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.37597984075546265},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07412412762641907},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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":4,"locations":[{"id":"doi:10.1109/waspaa.2017.8170034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/waspaa.2017.8170034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1709.07124","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.07124","pdf_url":"https://arxiv.org/pdf/1709.07124","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":"mag:2757279226","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/1709.07124","pdf_url":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1709.07124","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1709.07124","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1709.07124","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1709.07124","pdf_url":"https://arxiv.org/pdf/1709.07124","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":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2757279226.pdf","grobid_xml":"https://content.openalex.org/works/W2757279226.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1483064949","https://openalex.org/W1522301498","https://openalex.org/W1831449718","https://openalex.org/W1897240248","https://openalex.org/W1974774036","https://openalex.org/W2001987918","https://openalex.org/W2031647436","https://openalex.org/W2039844283","https://openalex.org/W2046869671","https://openalex.org/W2064675550","https://openalex.org/W2100556411","https://openalex.org/W2115706991","https://openalex.org/W2118103795","https://openalex.org/W2127851351","https://openalex.org/W2130789253","https://openalex.org/W2148575186","https://openalex.org/W2158252006","https://openalex.org/W2162514423","https://openalex.org/W2163312093","https://openalex.org/W2220485312","https://openalex.org/W2384495648","https://openalex.org/W2545232173","https://openalex.org/W2551814208","https://openalex.org/W2619204584","https://openalex.org/W2620139616","https://openalex.org/W3100774664","https://openalex.org/W3143596294","https://openalex.org/W6628781318","https://openalex.org/W6631190155","https://openalex.org/W6638670064","https://openalex.org/W6639532686","https://openalex.org/W6662385463","https://openalex.org/W6677645113","https://openalex.org/W6680012447","https://openalex.org/W6682889407","https://openalex.org/W6730022716"],"related_works":["https://openalex.org/W2964235918","https://openalex.org/W2949504522","https://openalex.org/W2750931658","https://openalex.org/W2526148220","https://openalex.org/W2764198198","https://openalex.org/W2963751183","https://openalex.org/W2804644188","https://openalex.org/W2788495591","https://openalex.org/W3090325430","https://openalex.org/W2794322104","https://openalex.org/W2915683453","https://openalex.org/W3087370605","https://openalex.org/W2999733888","https://openalex.org/W2896144487","https://openalex.org/W2937641152","https://openalex.org/W2112984492","https://openalex.org/W3123338478","https://openalex.org/W3122728801","https://openalex.org/W2005067285","https://openalex.org/W2891355459"],"abstract_inverted_index":{"In":[0],"this":[1,44],"paper,":[2],"we":[3],"propose":[4],"a":[5,23,125,134,161],"novel":[6],"recurrent":[7,48],"neural":[8],"network":[9,45,54,120],"architecture":[10,15,46],"for":[11,34],"speech":[12],"separation.":[13],"This":[14,79],"is":[16,105,140,167],"constructed":[17],"by":[18],"unfolding":[19],"the":[20,31,69,119],"iterations":[21],"of":[22,40,108,118,137,164],"sequential":[24],"iterative":[25],"soft-thresholding":[26],"algorithm":[27],"(ISTA)":[28],"that":[29,85],"solves":[30],"optimization":[32],"problem":[33],"sparse":[35,151],"nonnegative":[36],"matrix":[37],"factorization":[38],"(NMF)":[39],"spectrograms.":[41],"We":[42],"name":[43],"deep":[47,66,102],"NMF":[49,73,152],"(DR-NMF).":[50],"The":[51],"proposed":[52],"DR-NMF":[53,60,104,142,169],"has":[55],"three":[56],"distinct":[57],"advantages.":[58],"First,":[59],"provides":[61,82],"better":[62,92],"interpretability":[63,80],"than":[64,114],"other":[65],"architectures,":[67],"since":[68,116],"weights":[70],"correspond":[71],"to":[72,91,95,150,177],"model":[74],"parameters,":[75],"even":[76],"after":[77],"training.":[78],"also":[81],"principled":[83],"initializations":[84],"enable":[86],"faster":[87,110],"training":[88,138,165],"and":[89,146,153],"convergence":[90],"solutions":[93],"compared":[94,149,176],"conventional":[96],"random":[97],"initialization.":[98],"Second,":[99],"like":[100],"many":[101],"networks,":[103],"an":[106],"order":[107],"magnitude":[109],"at":[111,128],"test":[112],"time":[113,130],"NMF,":[115],"computation":[117],"output":[121],"only":[122],"requires":[123],"evaluating":[124],"few":[126],"layers":[127],"each":[129],"step.":[131],"Third,":[132],"when":[133],"limited":[135],"amount":[136,163],"data":[139,166],"available,":[141,168],"exhibits":[143],"stronger":[144],"generalization":[145],"separation":[147,174],"performance":[148,175],"state-of-the-art":[154],"long-short":[155],"term":[156],"memory":[157],"(LSTM)":[158],"networks.":[159,179],"When":[160],"large":[162],"achieves":[170],"lower":[171],"yet":[172],"competitive":[173],"LSTM":[178]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}