{"id":"https://openalex.org/W2988516171","doi":"https://doi.org/10.1109/icassp40776.2020.9053588","title":"End-To-End Non-Negative Autoencoders for Sound Source Separation","display_name":"End-To-End Non-Negative Autoencoders for Sound Source Separation","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W2988516171","doi":"https://doi.org/10.1109/icassp40776.2020.9053588","mag":"2988516171"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053588","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053588","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/1911.00102","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001842601","display_name":"Shrikant Venkataramani","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shrikant Venkataramani","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign","University of Illinois at Urbana\u2013Champaign, Department of Electrical and Computer Engineering"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"University of Illinois at Urbana\u2013Champaign, Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016864112","display_name":"Efthymios Tzinis","orcid":"https://orcid.org/0000-0002-1047-1338"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Efthymios Tzinis","raw_affiliation_strings":["Department of Computer Science, University of Illinois at Urbana-Champaign","[University of Illinois at Urbana-Champaign,Department of Computer Science]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Urbana-Champaign","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"[University of Illinois at Urbana-Champaign,Department of Computer Science]","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038903729","display_name":"Paris Smaragdis","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paris Smaragdis","raw_affiliation_strings":["Department of Computer Science, University of Illinois at Urbana-Champaign","[University of Illinois at Urbana-Champaign,Department of Computer Science]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Urbana-Champaign","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"[University of Illinois at Urbana-Champaign,Department of Computer Science]","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5001842601"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00762314,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"116","last_page":"120"},"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/T11309","display_name":"Music and Audio Processing","score":0.9994999766349792,"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":0.9983999729156494,"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/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.9180313348770142},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7599037885665894},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7464017868041992},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.7195122241973877},{"id":"https://openalex.org/keywords/modularity","display_name":"Modularity (biology)","score":0.6468387246131897},{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.6131730079650879},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.5835471153259277},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5505691170692444},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5245285630226135},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4729970097541809},{"id":"https://openalex.org/keywords/separation","display_name":"Separation (statistics)","score":0.44650885462760925},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.42713838815689087},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.414266973733902},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.41356968879699707},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.41198667883872986},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3403051197528839},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3266042172908783},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10847020149230957}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.9180313348770142},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7599037885665894},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7464017868041992},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.7195122241973877},{"id":"https://openalex.org/C2779478453","wikidata":"https://www.wikidata.org/wiki/Q6889748","display_name":"Modularity (biology)","level":2,"score":0.6468387246131897},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.6131730079650879},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.5835471153259277},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5505691170692444},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5245285630226135},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4729970097541809},{"id":"https://openalex.org/C2776061190","wikidata":"https://www.wikidata.org/wiki/Q7451805","display_name":"Separation (statistics)","level":2,"score":0.44650885462760925},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.42713838815689087},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.414266973733902},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.41356968879699707},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.41198667883872986},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3403051197528839},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3266042172908783},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10847020149230957},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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":5,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053588","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053588","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1911.00102","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.00102","pdf_url":"https://arxiv.org/pdf/1911.00102","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:2988516171","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1911.00102","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.1911.00102","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1911.00102","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"},{"id":"doi:10.17023/vk2g-mp07","is_oa":true,"landing_page_url":"https://doi.org/10.17023/vk2g-mp07","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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:1911.00102","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.00102","pdf_url":"https://arxiv.org/pdf/1911.00102","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":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7799999713897705}],"awards":[{"id":"https://openalex.org/G253909410","display_name":"CAREER:  Scaling Source Separation to Big Audio Data","funder_award_id":"1453104","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2988516171.pdf","grobid_xml":"https://content.openalex.org/works/W2988516171.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1790748249","https://openalex.org/W2039844283","https://openalex.org/W2086381917","https://openalex.org/W2104298926","https://openalex.org/W2113990625","https://openalex.org/W2114508388","https://openalex.org/W2127851351","https://openalex.org/W2150415460","https://openalex.org/W2221409856","https://openalex.org/W2460742184","https://openalex.org/W2519994964","https://openalex.org/W2774707525","https://openalex.org/W2894785362","https://openalex.org/W2903316710","https://openalex.org/W2911579794","https://openalex.org/W2918656717","https://openalex.org/W2920053118","https://openalex.org/W2944338086","https://openalex.org/W2952218014","https://openalex.org/W2962701080","https://openalex.org/W2962935966","https://openalex.org/W2962970934","https://openalex.org/W2963443859","https://openalex.org/W2963906950","https://openalex.org/W2964058413","https://openalex.org/W2969873628","https://openalex.org/W2971417062","https://openalex.org/W2998657200","https://openalex.org/W3098606562","https://openalex.org/W6688843265","https://openalex.org/W6744787216","https://openalex.org/W6746914816","https://openalex.org/W6760154766"],"related_works":["https://openalex.org/W3095999710","https://openalex.org/W2186043506","https://openalex.org/W2950354455","https://openalex.org/W2143564602","https://openalex.org/W3208297503","https://openalex.org/W2965379890","https://openalex.org/W2951070760","https://openalex.org/W3014611703","https://openalex.org/W3136180534","https://openalex.org/W2807036115","https://openalex.org/W2995541282","https://openalex.org/W3118307428","https://openalex.org/W3151900225","https://openalex.org/W2934576922","https://openalex.org/W2793768763","https://openalex.org/W3171477298","https://openalex.org/W3086646230","https://openalex.org/W3116321482","https://openalex.org/W3189569440","https://openalex.org/W2740098507"],"abstract_inverted_index":{"Discriminative":[0],"models":[1,24,85],"for":[2,77],"source":[3,46,78],"separation":[4,47,88],"have":[5],"recently":[6],"been":[7],"shown":[8],"to":[9,33,45,53,55,65,90],"produce":[10],"impressive":[11],"results.":[12],"However,":[13],"when":[14],"operating":[15],"on":[16],"sources":[17],"outside":[18],"of":[19,97,103],"the":[20,95,100],"training":[21],"set,":[22],"these":[23,84],"can":[25,49,74],"not":[26],"perform":[27],"as":[28],"well":[29],"and":[30,70,99],"are":[31],"cumbersome":[32],"update.":[34],"Classical":[35],"methods":[36],"like":[37],"Nonnegative":[38],"Matrix":[39],"Factorization":[40],"(NMF)":[41],"provide":[42],"modular":[43],"approaches":[44],"that":[48,83],"be":[50,75],"easily":[51],"updated":[52],"adapt":[54],"new":[56],"mixture":[57],"scenarios.":[58],"In":[59],"this":[60],"paper,":[61],"we":[62],"generalize":[63],"NMF":[64,98],"develop":[66],"end-to-end":[67],"non-negative":[68],"auto-encoders":[69],"demonstrate":[71],"how":[72],"they":[73],"used":[76],"separation.":[79],"Our":[80],"experiments":[81],"indicate":[82],"deliver":[86],"comparable":[87],"performance":[89],"discriminative":[91],"approaches,":[92],"while":[93],"retaining":[94],"modularity":[96],"modeling":[101],"flexibility":[102],"neural":[104],"networks.":[105]},"counts_by_year":[],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}