{"id":"https://openalex.org/W4206740369","doi":"https://doi.org/10.23919/eusipco54536.2021.9616016","title":"Adaptive Multi-Channel Signal Enhancement Based on Multi-Source Contribution Estimation","display_name":"Adaptive Multi-Channel Signal Enhancement Based on Multi-Source Contribution Estimation","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W4206740369","doi":"https://doi.org/10.23919/eusipco54536.2021.9616016"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco54536.2021.9616016","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco54536.2021.9616016","pdf_url":null,"source":{"id":"https://openalex.org/S4363607854","display_name":"2021 29th European Signal Processing Conference (EUSIPCO)","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 29th European Signal Processing Conference (EUSIPCO)","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/A5055065049","display_name":"Jacob Donley","orcid":"https://orcid.org/0000-0002-8401-798X"},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jacob Donley","raw_affiliation_strings":["Facebook Reality Labs Research, USA"],"affiliations":[{"raw_affiliation_string":"Facebook Reality Labs Research, USA","institution_ids":["https://openalex.org/I4210114444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026575041","display_name":"Vladimir Tourbabin","orcid":"https://orcid.org/0000-0003-2536-5666"},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vladimir Tourbabin","raw_affiliation_strings":["Facebook Reality Labs Research, USA"],"affiliations":[{"raw_affiliation_string":"Facebook Reality Labs Research, USA","institution_ids":["https://openalex.org/I4210114444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019518606","display_name":"Boaz Rafaely","orcid":"https://orcid.org/0000-0002-6819-9250"},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Boaz Rafaely","raw_affiliation_strings":["Facebook Reality Labs Research, USA"],"affiliations":[{"raw_affiliation_string":"Facebook Reality Labs Research, USA","institution_ids":["https://openalex.org/I4210114444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021251100","display_name":"Ravish Mehra","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ravish Mehra","raw_affiliation_strings":["Facebook Reality Labs Research, USA"],"affiliations":[{"raw_affiliation_string":"Facebook Reality Labs Research, USA","institution_ids":["https://openalex.org/I4210114444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5055065049"],"corresponding_institution_ids":["https://openalex.org/I4210114444"],"apc_list":null,"apc_paid":null,"fwci":0.172,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.42914708,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"276","last_page":"280"},"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/T11233","display_name":"Advanced Adaptive Filtering Techniques","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7930397987365723},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6161976456642151},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.6071974039077759},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5849481225013733},{"id":"https://openalex.org/keywords/source-separation","display_name":"Source separation","score":0.5631489753723145},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.539277970790863},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.4785269498825073},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4512183666229248},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.4294929504394531},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4053393304347992},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3876154124736786},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35069864988327026},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.2119966447353363},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09218171238899231}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7930397987365723},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6161976456642151},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.6071974039077759},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5849481225013733},{"id":"https://openalex.org/C2776864781","wikidata":"https://www.wikidata.org/wiki/Q52617913","display_name":"Source separation","level":2,"score":0.5631489753723145},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.539277970790863},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4785269498825073},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4512183666229248},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.4294929504394531},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4053393304347992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3876154124736786},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35069864988327026},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2119966447353363},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09218171238899231},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco54536.2021.9616016","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco54536.2021.9616016","pdf_url":null,"source":{"id":"https://openalex.org/S4363607854","display_name":"2021 29th European Signal Processing Conference (EUSIPCO)","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 29th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1984823839","https://openalex.org/W2106272332","https://openalex.org/W2127292597","https://openalex.org/W2146324387","https://openalex.org/W2147665979","https://openalex.org/W2163063500","https://openalex.org/W2398972335","https://openalex.org/W2507219293","https://openalex.org/W2568308529","https://openalex.org/W2795638445","https://openalex.org/W2891980359","https://openalex.org/W2892163332","https://openalex.org/W2898025984","https://openalex.org/W2918296821","https://openalex.org/W2937366654","https://openalex.org/W2952350176","https://openalex.org/W2964171275","https://openalex.org/W2973231102","https://openalex.org/W2998580368","https://openalex.org/W3015820460","https://openalex.org/W4210849719","https://openalex.org/W4289665794"],"related_works":["https://openalex.org/W1509813908","https://openalex.org/W2031820693","https://openalex.org/W3024816962","https://openalex.org/W973023320","https://openalex.org/W1910172735","https://openalex.org/W2118307209","https://openalex.org/W2107364365","https://openalex.org/W2539388437","https://openalex.org/W2107688514","https://openalex.org/W2137288760"],"abstract_inverted_index":{"Automated":[0],"solutions":[1],"to":[2,28,42,57,59,83,99,142],"multi-channel":[3],"signal":[4],"enhancement":[5,130],"for":[6,111,118,128],"improving":[7],"speech":[8,29],"communication":[9],"in":[10,92,146],"noisy":[11,147],"environments":[12],"has":[13],"become":[14],"a":[15,54,76,93,125],"popular":[16],"goal":[17],"among":[18],"the":[19,85,104,129,138,143],"research":[20],"community.":[21],"Many":[22],"proposed":[23,115],"approaches":[24],"focus":[25],"on":[26,32],"adapting":[27],"signals":[30,63,149],"based":[31],"their":[33,65,70],"temporal":[34,71],"characteristics":[35,106],"but":[36],"these":[37],"methods":[38],"are":[39],"primarily":[40],"limited":[41],"specific":[43],"types":[44],"of":[45,69,89,103,107,131,159],"desired":[46,60,120],"and":[47,61,121,150],"undesired":[48,62,122],"sound":[49],"sources.":[50],"This":[51],"paper":[52],"outlines":[53],"new":[55],"method":[56,74,116,139],"adapt":[58,141],"using":[64],"spatial":[66,105],"statistics,":[67],"independent":[68],"characteristics.":[72],"The":[73,114,133],"uses":[75],"linearly":[77],"constrained":[78],"minimum":[79],"variance":[80],"(LCMV)":[81],"beamformer":[82],"estimate":[84],"relative":[86],"source":[87,91,109,123,145],"contribution":[88],"each":[90,108],"mixture,":[94],"which":[95],"is":[96,156],"then":[97],"used":[98,110],"weight":[100],"statistical":[101],"estimates":[102],"final":[112],"separation.":[113],"allows":[117],"instantaneous":[119],"selection,":[124],"useful":[126],"ability":[127],"conversations.":[132],"simulated":[134],"results":[135],"show":[136],"that":[137,151],"can":[140],"targeted":[144],"mixture":[148],"under":[152],"realistic":[153],"conditions":[154],"it":[155],"also":[157],"capable":[158],"reaching":[160],"ideal":[161],"MVDR":[162],"performance.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}