{"id":"https://openalex.org/W4405440098","doi":"https://doi.org/10.1109/jstsp.2024.3518257","title":"Robust Channel Learning for Large-Scale Radio Speaker Verification","display_name":"Robust Channel Learning for Large-Scale Radio Speaker Verification","publication_year":2024,"publication_date":"2024-12-16","ids":{"openalex":"https://openalex.org/W4405440098","doi":"https://doi.org/10.1109/jstsp.2024.3518257"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2024.3518257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2024.3518257","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Signal Processing","raw_type":"journal-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/A5118899545","display_name":"Wenhao Yang","orcid":"https://orcid.org/0000-0003-1019-4446"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhao Yang","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-1019-4446","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027428789","display_name":"Jianguo Wei","orcid":"https://orcid.org/0000-0002-8964-9759"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianguo Wei","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-8964-9759","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082286929","display_name":"Wenhuan Lu","orcid":"https://orcid.org/0000-0002-7951-8907"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhuan Lu","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-7951-8907","affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440300","display_name":"Lei Li","orcid":"https://orcid.org/0000-0002-2929-0828"},"institutions":[{"id":"https://openalex.org/I124055696","display_name":"University of Copenhagen","ror":"https://ror.org/035b05819","country_code":"DK","type":"education","lineage":["https://openalex.org/I124055696"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Lei Li","raw_affiliation_strings":["Department of Computer Science, University of Copenhagen, Copenhagen, Denmark"],"raw_orcid":"https://orcid.org/0000-0002-2929-0828","affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Copenhagen, Copenhagen, Denmark","institution_ids":["https://openalex.org/I124055696"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034792613","display_name":"Xugang Lu","orcid":"https://orcid.org/0000-0001-7075-448X"},"institutions":[{"id":"https://openalex.org/I90023481","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349","country_code":"JP","type":"facility","lineage":["https://openalex.org/I90023481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xugang Lu","raw_affiliation_strings":["National Institute of Information and Communications Technology, Kyoto, Japan"],"raw_orcid":"https://orcid.org/0000-0001-7075-448X","affiliations":[{"raw_affiliation_string":"National Institute of Information and Communications Technology, Kyoto, Japan","institution_ids":["https://openalex.org/I90023481"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0606,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.76852231,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"19","issue":"1","first_page":"248","last_page":"259"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9994999766349792,"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"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9871000051498413,"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":0.7260144948959351},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.532245397567749},{"id":"https://openalex.org/keywords/radio-channel","display_name":"Radio channel","score":0.5304989814758301},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5128860473632812},{"id":"https://openalex.org/keywords/speaker-verification","display_name":"Speaker verification","score":0.5122055411338806},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4818071722984314},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.40755099058151245},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3568670153617859},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.2479248344898224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7260144948959351},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.532245397567749},{"id":"https://openalex.org/C2988879021","wikidata":"https://www.wikidata.org/wiki/Q273623","display_name":"Radio channel","level":3,"score":0.5304989814758301},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5128860473632812},{"id":"https://openalex.org/C2982762665","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker verification","level":3,"score":0.5122055411338806},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4818071722984314},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.40755099058151245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3568670153617859},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.2479248344898224},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstsp.2024.3518257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2024.3518257","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/a81169aa-9169-46fd-803f-ad7ea9f50438","is_oa":false,"landing_page_url":"https://researchprofiles.ku.dk/da/publications/a81169aa-9169-46fd-803f-ad7ea9f50438","pdf_url":null,"source":{"id":"https://openalex.org/S4306401983","display_name":"Research at the University of Copenhagen (University of Copenhagen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I124055696","host_organization_name":"University of Copenhagen","host_organization_lineage":["https://openalex.org/I124055696"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Yang , W , Wei , J , Lu , W , Li , L & Lu , X 2025 , ' Robust Channel Learning for Large-Scale Radio Speaker Verification ' , IEEE Journal on Selected Topics in Signal Processing , vol. 19 , no. 1 , pp. 248-259 . https://doi.org/10.1109/JSTSP.2024.3518257","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W1490756768","https://openalex.org/W1494198834","https://openalex.org/W1589137271","https://openalex.org/W1731081199","https://openalex.org/W2002341000","https://openalex.org/W2046015436","https://openalex.org/W2073017590","https://openalex.org/W2078953162","https://openalex.org/W2079623482","https://openalex.org/W2094356263","https://openalex.org/W2095705004","https://openalex.org/W2219249508","https://openalex.org/W2403409912","https://openalex.org/W2405476549","https://openalex.org/W2622599113","https://openalex.org/W2747165665","https://openalex.org/W2784163702","https://openalex.org/W2801581493","https://openalex.org/W2885724687","https://openalex.org/W2890964092","https://openalex.org/W2901368553","https://openalex.org/W2916104401","https://openalex.org/W2936774411","https://openalex.org/W2962914040","https://openalex.org/W2963242190","https://openalex.org/W2963446838","https://openalex.org/W2964154960","https://openalex.org/W2969985801","https://openalex.org/W2972315886","https://openalex.org/W2973154337","https://openalex.org/W3015306128","https://openalex.org/W3015503328","https://openalex.org/W3015546017","https://openalex.org/W3015555484","https://openalex.org/W3015598461","https://openalex.org/W3015611708","https://openalex.org/W3015964387","https://openalex.org/W3016258016","https://openalex.org/W3024869864","https://openalex.org/W3081285175","https://openalex.org/W3097224504","https://openalex.org/W3103152812","https://openalex.org/W3154451338","https://openalex.org/W3160743249","https://openalex.org/W3160744627","https://openalex.org/W3163421828","https://openalex.org/W3167533889","https://openalex.org/W3201059441","https://openalex.org/W3209059054","https://openalex.org/W3209984917","https://openalex.org/W4221144444","https://openalex.org/W4372266902","https://openalex.org/W4372340947","https://openalex.org/W4372349064","https://openalex.org/W4376456958","https://openalex.org/W4382602944","https://openalex.org/W4385823321","https://openalex.org/W4387704395","https://openalex.org/W4392904642","https://openalex.org/W6629408151","https://openalex.org/W6637618735","https://openalex.org/W6674330103","https://openalex.org/W6688816777","https://openalex.org/W6752888775","https://openalex.org/W6753916174","https://openalex.org/W6769867024","https://openalex.org/W6780218876","https://openalex.org/W6853723667","https://openalex.org/W6917408469"],"related_works":["https://openalex.org/W1491159402","https://openalex.org/W66821593","https://openalex.org/W4297807400","https://openalex.org/W2249138175","https://openalex.org/W1521299571","https://openalex.org/W4313854686","https://openalex.org/W3162054169","https://openalex.org/W1813780412","https://openalex.org/W1516392727","https://openalex.org/W2140022733"],"abstract_inverted_index":{"Recent":[0],"research":[1],"in":[2,23,86,171],"speaker":[3,61,151,172],"verification":[4,62,152,173],"has":[5],"increasingly":[6],"focused":[7],"on":[8],"achieving":[9],"robust":[10],"and":[11,18,37,69,125,142,164],"reliable":[12],"recognition":[13],"under":[14],"challenging":[15],"channel":[16],"conditions":[17],"noisy":[19],"environments.":[20],"Identifying":[21],"speakers":[22],"radio":[24,87,139,149,169],"communications":[25],"is":[26],"particularly":[27],"difficult":[28],"due":[29],"to":[30],"inherent":[31],"limitations":[32],"such":[33],"as":[34],"constrained":[35],"bandwidth":[36,84,93],"pervasive":[38],"noise":[39,101,104],"interference.":[40],"To":[41],"address":[42],"this":[43],"issue,":[44],"we":[45,110,131],"present":[46],"a":[47,133,137,144],"Channel":[48],"Robust":[49],"Speaker":[50],"Learning":[51],"(CRSL)":[52],"framework":[53,77],"that":[54,82,116,157],"enhances":[55,162],"the":[56,59,70,92,106,118],"robustness":[57],"of":[58,72,94,128],"current":[60],"pipeline,":[63],"considering":[64],"data":[65,67],"source,":[66],"augmentation,":[68],"efficiency":[71],"model":[73],"transfer":[74],"processes.":[75],"Our":[76],"introduces":[78],"an":[79,112],"augmentation":[80],"module":[81],"mitigates":[83,165],"variations":[85],"speech":[88,140],"datasets":[89],"by":[90,102,168],"manipulating":[91],"training":[95,123],"inputs.":[96],"It":[97],"also":[98],"addresses":[99],"unknown":[100],"introducing":[103],"within":[105],"manifold":[107],"space.":[108],"Additionally,":[109],"propose":[111],"efficient":[113],"fine-tuning":[114],"method":[115],"reduces":[117],"need":[119],"for":[120,135,148],"extensive":[121],"additional":[122],"time":[124],"large":[126],"amounts":[127],"data.":[129],"Moreover,":[130],"develop":[132],"toolkit":[134],"assembling":[136],"large-scale":[138],"corpus":[141],"establish":[143],"benchmark":[145],"specifically":[146],"tailored":[147],"scenario":[150],"studies.":[153],"Experimental":[154],"results":[155],"demonstrate":[156],"our":[158],"proposed":[159],"methodology":[160],"effectively":[161],"performance":[163],"degradation":[166],"caused":[167],"transmission":[170],"tasks.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}