{"id":"https://openalex.org/W4235050345","doi":"https://doi.org/10.1109/mmsp53017.2021.9733494","title":"Ambisonics domain Singing Voice Separation combining Deep Neural Network and Direction Aware Multichannel NMF","display_name":"Ambisonics domain Singing Voice Separation combining Deep Neural Network and Direction Aware Multichannel NMF","publication_year":2021,"publication_date":"2021-10-06","ids":{"openalex":"https://openalex.org/W4235050345","doi":"https://doi.org/10.1109/mmsp53017.2021.9733494"},"language":"en","primary_location":{"id":"doi:10.1109/mmsp53017.2021.9733494","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp53017.2021.9733494","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-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/A5024808450","display_name":"Antonio J. Mu\u00f1oz-Montoro","orcid":"https://orcid.org/0000-0001-9518-8955"},"institutions":[{"id":"https://openalex.org/I165339363","display_name":"Universidad de Oviedo","ror":"https://ror.org/006gksa02","country_code":"ES","type":"education","lineage":["https://openalex.org/I165339363"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Antonio J. Mu\u00f1oz-Montoro","raw_affiliation_strings":["Universidad de Oviedo,Computer Science Department,Gijón,Spain"],"affiliations":[{"raw_affiliation_string":"Universidad de Oviedo,Computer Science Department,Gijón,Spain","institution_ids":["https://openalex.org/I165339363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031959992","display_name":"Julio J. Carabias-Orti","orcid":"https://orcid.org/0000-0002-6296-1101"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Julio J. Carabias-Orti","raw_affiliation_strings":["Universidad de Jaén,Telecommunication Engineering Department,Jaén,Spain"],"affiliations":[{"raw_affiliation_string":"Universidad de Jaén,Telecommunication Engineering Department,Jaén,Spain","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064887627","display_name":"P. Vera\u2010Candeas","orcid":"https://orcid.org/0000-0003-0866-703X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pedro Vera-Candeas","raw_affiliation_strings":["Universidad de Jaén,Telecommunication Engineering Department,Jaén,Spain"],"affiliations":[{"raw_affiliation_string":"Universidad de Jaén,Telecommunication Engineering Department,Jaén,Spain","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5024808450"],"corresponding_institution_ids":["https://openalex.org/I165339363"],"apc_list":null,"apc_paid":null,"fwci":1.2189,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.80121704,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"98","issue":null,"first_page":"1","last_page":"6"},"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":0.9983999729156494,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9977999925613403,"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/ambisonics","display_name":"Ambisonics","score":0.8408677577972412},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.7467653155326843},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7441767454147339},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.718185544013977},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.7016425728797913},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5128777027130127},{"id":"https://openalex.org/keywords/beamforming","display_name":"Beamforming","score":0.48927637934684753},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4758017957210541},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.46341389417648315},{"id":"https://openalex.org/keywords/direction-of-arrival","display_name":"Direction of arrival","score":0.45918816328048706},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.458133727312088},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4148627519607544},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32694411277770996},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.2834465801715851},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.26398319005966187},{"id":"https://openalex.org/keywords/loudspeaker","display_name":"Loudspeaker","score":0.15662193298339844}],"concepts":[{"id":"https://openalex.org/C47726159","wikidata":"https://www.wikidata.org/wiki/Q457547","display_name":"Ambisonics","level":3,"score":0.8408677577972412},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.7467653155326843},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7441767454147339},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.718185544013977},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.7016425728797913},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5128777027130127},{"id":"https://openalex.org/C54197355","wikidata":"https://www.wikidata.org/wiki/Q5782992","display_name":"Beamforming","level":2,"score":0.48927637934684753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4758017957210541},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.46341389417648315},{"id":"https://openalex.org/C172051844","wikidata":"https://www.wikidata.org/wiki/Q5280438","display_name":"Direction of arrival","level":3,"score":0.45918816328048706},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.458133727312088},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4148627519607544},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32694411277770996},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.2834465801715851},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.26398319005966187},{"id":"https://openalex.org/C157138929","wikidata":"https://www.wikidata.org/wiki/Q570","display_name":"Loudspeaker","level":2,"score":0.15662193298339844},{"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/C21822782","wikidata":"https://www.wikidata.org/wiki/Q131214","display_name":"Antenna (radio)","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mmsp53017.2021.9733494","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp53017.2021.9733494","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:ruja.ujaen.es:10953/7408","is_oa":false,"landing_page_url":"https://doi.org/10.1109/MMSP53017.2021.9733494","pdf_url":null,"source":{"id":"https://openalex.org/S4306401039","display_name":"RUJA (Universidad de Ja\u00e9n)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I191420491","host_organization_name":"Universidad de Ja\u00e9n","host_organization_lineage":["https://openalex.org/I191420491"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/acceptedVersion"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322930","display_name":"Ministerio de Ciencia e Innovaci\u00f3n","ror":"https://ror.org/034900433"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2021196544","https://openalex.org/W2026034143","https://openalex.org/W2068700550","https://openalex.org/W2075107327","https://openalex.org/W2105921478","https://openalex.org/W2113990625","https://openalex.org/W2119494071","https://openalex.org/W2168273590","https://openalex.org/W2408744528","https://openalex.org/W2587994092","https://openalex.org/W2783831488","https://openalex.org/W2801528485","https://openalex.org/W2899857465","https://openalex.org/W2913140522","https://openalex.org/W2942172990","https://openalex.org/W2963191020","https://openalex.org/W2963452667","https://openalex.org/W2963992487","https://openalex.org/W2964005873","https://openalex.org/W2979850772","https://openalex.org/W2982151328","https://openalex.org/W3015788098","https://openalex.org/W3025423009","https://openalex.org/W3115341864","https://openalex.org/W3117355944","https://openalex.org/W3117609054","https://openalex.org/W3160140981","https://openalex.org/W6747747266","https://openalex.org/W6751512325","https://openalex.org/W6777639356"],"related_works":["https://openalex.org/W2551137307","https://openalex.org/W2113526703","https://openalex.org/W2123043102","https://openalex.org/W2577807713","https://openalex.org/W3094316140","https://openalex.org/W3133205200","https://openalex.org/W2547262076","https://openalex.org/W2098101267","https://openalex.org/W2563421448","https://openalex.org/W2898145319"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,33,77,87,96,123],"problem":[4],"of":[5,51,80,98,106],"multichannel":[6,16,70,129],"source":[7,28,57,82],"separation":[8,101],"in":[9,83],"ambisonics":[10,108],"signals":[11,109],"combining":[12],"two":[13],"powerful":[14],"approaches,":[15],"NMF":[17],"with":[18,40,102],"recent":[19],"single-channel":[20],"deep":[21],"learning":[22],"(DL)":[23],"based":[24,68],"spectrum":[25],"inference.":[26],"Individual":[27],"spectra":[29],"are":[30,59],"estimated":[31],"from":[32],"zero-order":[34],"(omnidirectional)":[35],"spherical":[36],"harmonic":[37],"(SH)":[38],"signal":[39],"a":[41,52,62,103],"Masker-Denoiser":[42],"twin":[43],"network,":[44],"able":[45],"to":[46,85],"model":[47,67],"long-term":[48],"temporal":[49],"patterns":[50],"musical":[53],"piece.":[54],"The":[55,90],"initialized":[56],"spectrograms":[58],"used":[60],"within":[61],"SHdomain":[63],"spatial":[64,78],"covariance":[65],"mixing":[66],"on":[69,95],"non-negative":[71],"matrix":[72],"factorization":[73],"(MNMF)":[74],"that":[75,116],"predicts":[76],"characteristics":[79],"each":[81],"order":[84],"refine":[86],"network":[88],"prediction.":[89],"proposed":[91],"framework":[92],"is":[93],"evaluated":[94],"task":[97],"singing":[99],"voice":[100],"large":[104],"dataset":[105],"simulated":[107],"using":[110],"several":[111],"setups.":[112],"Experimental":[113],"results":[114],"show":[115],"our":[117],"joint":[118],"DL+SH-MNMF":[119],"method":[120],"outperforms":[121],"both":[122],"individual":[124],"monophonic":[125],"DL-based":[126],"separation,":[127],"baseline":[128],"MNMF":[130],"and":[131],"SH":[132],"domain":[133],"beamforming":[134],"classical":[135],"methods.":[136]},"counts_by_year":[{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}