{"id":"https://openalex.org/W3134831347","doi":"https://doi.org/10.1186/s13634-021-00762-2","title":"Text-independent speaker recognition based on adaptive course learning loss and deep residual network","display_name":"Text-independent speaker recognition based on adaptive course learning loss and deep residual network","publication_year":2021,"publication_date":"2021-07-23","ids":{"openalex":"https://openalex.org/W3134831347","doi":"https://doi.org/10.1186/s13634-021-00762-2","mag":"3134831347"},"language":"en","primary_location":{"id":"doi:10.1186/s13634-021-00762-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-021-00762-2","pdf_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-021-00762-2","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-021-00762-2","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062285356","display_name":"Qinghua Zhong","orcid":"https://orcid.org/0000-0001-6985-1610"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qinghua Zhong","raw_affiliation_strings":["School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, 510006, China","South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, 510006, China","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079142884","display_name":"Ruining Dai","orcid":"https://orcid.org/0000-0002-7354-6608"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruining Dai","raw_affiliation_strings":["School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, 510006, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, 510006, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100399305","display_name":"Han Zhang","orcid":"https://orcid.org/0009-0000-2090-374X"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Zhang","raw_affiliation_strings":["School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, 510006, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, 510006, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100732888","display_name":"Yongsheng Zhu","orcid":"https://orcid.org/0000-0002-1378-8939"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongsheng Zhu","raw_affiliation_strings":["School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, 510006, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, 510006, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074205617","display_name":"Guofu Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guofu Zhou","raw_affiliation_strings":["South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China"],"affiliations":[{"raw_affiliation_string":"South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, China","institution_ids":["https://openalex.org/I187400657"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5062285356"],"corresponding_institution_ids":["https://openalex.org/I187400657"],"apc_list":{"value":1140,"currency":"GBP","value_usd":1398},"apc_paid":{"value":1140,"currency":"GBP","value_usd":1398},"fwci":0.8399,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.77819784,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2021","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998000264167786,"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/T10860","display_name":"Speech and Audio Processing","score":0.998199999332428,"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":0.9958000183105469,"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/softmax-function","display_name":"Softmax function","score":0.8222978711128235},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.797982931137085},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.6018186807632446},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5919473767280579},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5888553857803345},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5877353549003601},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.5608157515525818},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4583330750465393},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.45364969968795776},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43109622597694397},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3915420174598694},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28371375799179077},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13786503672599792}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.8222978711128235},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.797982931137085},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.6018186807632446},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5919473767280579},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5888553857803345},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5877353549003601},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.5608157515525818},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4583330750465393},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.45364969968795776},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43109622597694397},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3915420174598694},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28371375799179077},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13786503672599792}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s13634-021-00762-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-021-00762-2","pdf_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-021-00762-2","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3e73ef6e70f84b37bc9b50075c435ebb","is_oa":true,"landing_page_url":"https://doaj.org/article/3e73ef6e70f84b37bc9b50075c435ebb","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EURASIP Journal on Advances in Signal Processing, Vol 2021, Iss 1, Pp 1-16 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s13634-021-00762-2","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13634-021-00762-2","pdf_url":"https://asp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13634-021-00762-2","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.550000011920929}],"awards":[{"id":"https://openalex.org/G1051660574","display_name":null,"funder_award_id":"2019A151","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G1607257392","display_name":null,"funder_award_id":"2019050001","funder_id":"https://openalex.org/F4320335795","funder_display_name":"Science and Technology Planning Project of Guangdong Province"},{"id":"https://openalex.org/G2023741321","display_name":null,"funder_award_id":"2019050001","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G3319757353","display_name":null,"funder_award_id":"2016TQ03","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G3964740569","display_name":null,"funder_award_id":"2019A1515011940","funder_id":"https://openalex.org/F4320335795","funder_display_name":"Science and Technology Planning Project of Guangdong Province"},{"id":"https://openalex.org/G4806558672","display_name":null,"funder_award_id":"202002030353","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G6229747645","display_name":null,"funder_award_id":"2017B030308009","funder_id":"https://openalex.org/F4320335795","funder_display_name":"Science and Technology Planning Project of Guangdong Province"},{"id":"https://openalex.org/G7323496340","display_name":null,"funder_award_id":"2019A1515011940","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G7543324836","display_name":null,"funder_award_id":"2019A15150","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320335795","display_name":"Science and Technology Planning Project of Guangdong Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3134831347.pdf","grobid_xml":"https://content.openalex.org/works/W3134831347.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1936725236","https://openalex.org/W1996512145","https://openalex.org/W2078169166","https://openalex.org/W2080794664","https://openalex.org/W2129244720","https://openalex.org/W2194775991","https://openalex.org/W2594407953","https://openalex.org/W2726515241","https://openalex.org/W2747238065","https://openalex.org/W2784163702","https://openalex.org/W2794506738","https://openalex.org/W2802973008","https://openalex.org/W2806743950","https://openalex.org/W2808631503","https://openalex.org/W2811153427","https://openalex.org/W2901855206","https://openalex.org/W2916104401","https://openalex.org/W2940070181","https://openalex.org/W2946508582","https://openalex.org/W2946615417","https://openalex.org/W2951758756","https://openalex.org/W2955210370","https://openalex.org/W2956925952","https://openalex.org/W2963702081","https://openalex.org/W2969985801","https://openalex.org/W2970827607","https://openalex.org/W2981087920","https://openalex.org/W3005759882","https://openalex.org/W3008353833","https://openalex.org/W3010925296","https://openalex.org/W3013020904","https://openalex.org/W3016912202","https://openalex.org/W3035693354","https://openalex.org/W3036173644","https://openalex.org/W3096235116","https://openalex.org/W3103152812"],"related_works":["https://openalex.org/W3095152779","https://openalex.org/W3119773509","https://openalex.org/W3128220219","https://openalex.org/W2982889384","https://openalex.org/W4226227567","https://openalex.org/W2971218105","https://openalex.org/W3006353185","https://openalex.org/W3010284783","https://openalex.org/W4287113729","https://openalex.org/W3173314472"],"abstract_inverted_index":{"Abstract":[0],"Text-independent":[1],"speaker":[2,44,95,187,217],"recognition":[3,9,32,45,188,218],"is":[4],"widely":[5],"used":[6,150],"in":[7,54],"identity":[8],"that":[10],"has":[11,130],"a":[12,40,64,69,101,107,120,125,180],"wide":[13],"spectrum":[14],"of":[15,34,42,63],"applications,":[16],"such":[17,133],"as":[18,134],"criminal":[19],"investigation,":[20],"payment":[21],"certification,":[22],"and":[23,68,106,146,161,172,190,208,234],"interest-based":[24],"customer":[25],"services.":[26],"In":[27],"order":[28],"to":[29,104,111,142,157,179],"improve":[30],"the":[31,84,113,135,144,159],"ability":[33],"log":[35],"filter":[36],"bank":[37],"feature":[38,115],"vectors,":[39],"method":[41,176],"text-independent":[43,186],"based":[46],"on":[47,199,204,210,225,230,236],"deep":[48,58,97],"residual":[49,59,65,98],"networks":[50,99],"model":[51],"was":[52,61,100,110,177,221],"proposed":[53,175],"this":[55,168],"paper.":[56],"The":[57,76,174],"network":[60,66,117],"composed":[62],"(ResNet)":[67],"convolutional":[70],"attention":[71],"statistics":[72],"pooling":[73],"(CASP)":[74],"layer.":[75],"CASP":[77],"layer":[78],"could":[79,196],"aggregate":[80],"frame-level":[81],"features":[82,92],"from":[83],"ResNet":[85],"into":[86],"an":[87,151],"utterance-level":[88],"features.":[89],"Extracting":[90],"speech":[91],"for":[93,167,184],"each":[94],"using":[96,119],"promising":[102],"direction":[103],"explore,":[105],"straightforward":[108],"solution":[109],"train":[112],"discriminative":[114],"extraction":[116],"by":[118,223],"margin-based":[121,126,165],"loss":[122,127,155],"function.":[123],"However,":[124],"function":[128],"often":[129],"certain":[131],"limitations,":[132],"margins":[136],"between":[137],"different":[138,164],"categories":[139],"were":[140],"set":[141],"be":[143],"same":[145],"fixed.":[147],"Thus,":[148],"we":[149],"adaptive":[152],"curriculum":[153],"learning":[154],"(ACLL)":[156],"address":[158],"problem":[160],"introduce":[162],"two":[163],"losses":[166],"problem,":[169],"i.e.,":[170],"AM-Softmax":[171],"AAM-Softmax.":[173],"applied":[178],"large-scale":[181],"VoxCeleb2":[182],"dataset":[183],"extensive":[185],"experiments,":[189],"average":[191],"equal":[192],"error":[193],"rate":[194],"(EER)":[195],"achieve":[197],"1.76%":[198],"VoxCeleb1":[200,226],"test":[201,206,212,227,232,238],"dataset,":[202,207,228,233],"1.91%":[203],"VoxCeleb1-E":[205,231],"3.24%":[209],"VoxCeleb1-H":[211,237],"dataset.":[213,239],"Compared":[214],"with":[215],"related":[216],"methods,":[219],"EER":[220],"improved":[222],"1.11%":[224],"1.04%":[229],"1.69%":[235]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}