{"id":"https://openalex.org/W4416251151","doi":"https://doi.org/10.1109/waspaa66052.2025.11230930","title":"Controlling the Parameterized Multi-channel Wiener Filter using a tiny neural network","display_name":"Controlling the Parameterized Multi-channel Wiener Filter using a tiny neural network","publication_year":2025,"publication_date":"2025-10-12","ids":{"openalex":"https://openalex.org/W4416251151","doi":"https://doi.org/10.1109/waspaa66052.2025.11230930"},"language":null,"primary_location":{"id":"doi:10.1109/waspaa66052.2025.11230930","is_oa":false,"landing_page_url":"https://doi.org/10.1109/waspaa66052.2025.11230930","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5011673214","display_name":"Eric Grinstein","orcid":"https://orcid.org/0000-0003-4502-5407"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Eric Grinstein","raw_affiliation_strings":["Imperial College London,U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College London,U.K","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050492887","display_name":"Ashutosh Pandey","orcid":"https://orcid.org/0000-0002-3352-7453"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ashutosh Pandey","raw_affiliation_strings":["Meta Reality Labs"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta Reality Labs","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047088317","display_name":"Chaojie Li","orcid":"https://orcid.org/0000-0001-6874-3052"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cole Li","raw_affiliation_strings":["Meta Reality Labs"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta Reality Labs","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001132035","display_name":"S. Srivatsa Srinivas","orcid":"https://orcid.org/0000-0003-1169-2666"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shanmukha Srinivas","raw_affiliation_strings":["Ohio State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011286001","display_name":"Juan Azcarreta","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Juan Azcarreta","raw_affiliation_strings":["Meta Reality Labs"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta Reality Labs","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055065049","display_name":"Jacob Donley","orcid":"https://orcid.org/0000-0002-8401-798X"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jacob Donley","raw_affiliation_strings":["Meta Reality Labs"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta Reality Labs","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101421510","display_name":"Sanha Lee","orcid":"https://orcid.org/0000-0002-1125-9814"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sanha Lee","raw_affiliation_strings":["Meta Reality Labs"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta Reality Labs","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058219648","display_name":"Ali Aroudi","orcid":"https://orcid.org/0000-0001-5770-0858"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ali Aroudi","raw_affiliation_strings":["Meta Reality Labs"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta Reality Labs","institution_ids":["https://openalex.org/I4210128585"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020934947","display_name":"\u00c7a\u011fda\u015f Bilen","orcid":"https://orcid.org/0000-0002-2176-2720"},"institutions":[{"id":"https://openalex.org/I4210128585","display_name":"META Health","ror":"https://ror.org/035h67p10","country_code":"US","type":"other","lineage":["https://openalex.org/I4210128585"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"\u00c7a\u011fda\u015f Bilen","raw_affiliation_strings":["Meta Reality Labs"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meta Reality Labs","institution_ids":["https://openalex.org/I4210128585"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9945999979972839,"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":0.9945999979972839,"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":0.004000000189989805,"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/T10283","display_name":"Hearing Loss and Rehabilitation","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/wiener-filter","display_name":"Wiener filter","score":0.6879000067710876},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.6089000105857849},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5976999998092651},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5871000289916992},{"id":"https://openalex.org/keywords/speech-enhancement","display_name":"Speech enhancement","score":0.5814999938011169},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5722000002861023},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5450000166893005},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5151000022888184}],"concepts":[{"id":"https://openalex.org/C18537770","wikidata":"https://www.wikidata.org/wiki/Q25523","display_name":"Wiener filter","level":2,"score":0.6879000067710876},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6248999834060669},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.6089000105857849},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5976999998092651},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5891000032424927},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5871000289916992},{"id":"https://openalex.org/C2776182073","wikidata":"https://www.wikidata.org/wiki/Q7575395","display_name":"Speech enhancement","level":3,"score":0.5814999938011169},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5722000002861023},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5450000166893005},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5151000022888184},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4465000033378601},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.421999990940094},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.37070000171661377},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.36469998955726624},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.35100001096725464},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.34860000014305115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34529998898506165},{"id":"https://openalex.org/C100675267","wikidata":"https://www.wikidata.org/wiki/Q1371624","display_name":"Background noise","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C15652857","wikidata":"https://www.wikidata.org/wiki/Q599016","display_name":"Wiener deconvolution","level":4,"score":0.3018999993801117},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26660001277923584},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.2590999901294708},{"id":"https://openalex.org/C22597639","wikidata":"https://www.wikidata.org/wiki/Q5449227","display_name":"Filter design","level":3,"score":0.25870001316070557}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/waspaa66052.2025.11230930","is_oa":false,"landing_page_url":"https://doi.org/10.1109/waspaa66052.2025.11230930","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W653761051","https://openalex.org/W1483052920","https://openalex.org/W1552314771","https://openalex.org/W1976805820","https://openalex.org/W2066218102","https://openalex.org/W2077639267","https://openalex.org/W2101609516","https://openalex.org/W2117678320","https://openalex.org/W2126942983","https://openalex.org/W2127292597","https://openalex.org/W2127851351","https://openalex.org/W2141998673","https://openalex.org/W2146324387","https://openalex.org/W2155112232","https://openalex.org/W2166117654","https://openalex.org/W2168729028","https://openalex.org/W2486913545","https://openalex.org/W2568308529","https://openalex.org/W2763188033","https://openalex.org/W2889442120","https://openalex.org/W2892163332","https://openalex.org/W2972335649","https://openalex.org/W2991361823","https://openalex.org/W3009032512","https://openalex.org/W3015791598","https://openalex.org/W3097906045","https://openalex.org/W3134695619","https://openalex.org/W3147539069","https://openalex.org/W4286896457","https://openalex.org/W4311187069","https://openalex.org/W4312701366","https://openalex.org/W4321608474","https://openalex.org/W4385975756","https://openalex.org/W4392902607","https://openalex.org/W4392903047","https://openalex.org/W4392903568","https://openalex.org/W4402112139","https://openalex.org/W4403127014","https://openalex.org/W4408352921"],"related_works":[],"abstract_inverted_index":{"Noise":[0],"suppression":[1],"and":[2,87,103],"speech":[3,34,89,105],"distortion":[4],"are":[5],"two":[6],"important":[7],"aspects":[8],"to":[9,109],"be":[10],"balanced":[11],"when":[12],"designing":[13],"multi-channel":[14],"Speech":[15],"Enhancement":[16],"(SE)":[17],"algorithms.":[18],"Although":[19],"neural":[20,76],"network":[21],"models":[22],"have":[23],"achieved":[24],"state-of-the-art":[25],"noise":[26,85],"suppression,":[27],"their":[28],"non-linear":[29],"operations":[30],"often":[31],"introduce":[32],"high":[33,84],"distortion.":[35,90],"Conversely,":[36],"classical":[37],"signal":[38],"processing":[39],"algorithms":[40],"such":[41],"as":[42],"the":[43,55,67],"Parameterized":[44],"Multi-channel":[45],"Wiener":[46],"Filter":[47],"(PMWF)":[48],"beamformer":[49],"offer":[50],"explicit":[51],"mechanisms":[52],"for":[53],"controlling":[54],"suppression/distortion":[56],"trade-off.":[57],"In":[58],"this":[59],"work,":[60],"we":[61],"present":[62],"NeuralPMWF,":[63],"a":[64,73,80],"system":[65,82],"where":[66],"PMWF":[68],"is":[69],"entirely":[70],"controlled":[71],"using":[72,113],"low-latency,":[74],"low-compute":[75],"network,":[77],"resulting":[78],"in":[79,99,107],"low-complexity":[81],"offering":[83],"reduction":[86],"low":[88],"Experimental":[91],"results":[92,98],"show":[93],"that":[94],"our":[95],"proposed":[96],"approach":[97],"significantly":[100],"better":[101],"perceptual":[102],"objective":[104],"enhancement":[106],"comparison":[108],"several":[110],"competitive":[111],"baselines":[112],"similar":[114],"computational":[115],"resources.":[116]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}
