{"id":"https://openalex.org/W4405709823","doi":"https://doi.org/10.1109/iscslp63861.2024.10800283","title":"Combining Self-Supervised Learning and Adversarial Training Based Domain Adaptation for Speaker Verification","display_name":"Combining Self-Supervised Learning and Adversarial Training Based Domain Adaptation for Speaker Verification","publication_year":2024,"publication_date":"2024-11-07","ids":{"openalex":"https://openalex.org/W4405709823","doi":"https://doi.org/10.1109/iscslp63861.2024.10800283"},"language":"en","primary_location":{"id":"doi:10.1109/iscslp63861.2024.10800283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscslp63861.2024.10800283","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 14th International Symposium on Chinese Spoken Language Processing (ISCSLP)","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/A5101416769","display_name":"Zhengyang Chen","orcid":"https://orcid.org/0000-0003-1293-8146"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhengyang Chen","raw_affiliation_strings":["AI Institute, Shanghai Jiao Tong University,Auditory Cognition and Computational Acoustics Lab, MoE Key Lab of Artificial Intelligence,Department of Computer Science and Engineering,Shanghai"],"affiliations":[{"raw_affiliation_string":"AI Institute, Shanghai Jiao Tong University,Auditory Cognition and Computational Acoustics Lab, MoE Key Lab of Artificial Intelligence,Department of Computer Science and Engineering,Shanghai","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055716987","display_name":"Shuai Wang","orcid":"https://orcid.org/0000-0002-1796-7280"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Wang","raw_affiliation_strings":["Shenzhen Research Institute of Big Data,Shenzhen"],"affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data,Shenzhen","institution_ids":["https://openalex.org/I4210099586"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076786676","display_name":"Bing Han","orcid":"https://orcid.org/0000-0001-6095-9422"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Han","raw_affiliation_strings":["AI Institute, Shanghai Jiao Tong University,Auditory Cognition and Computational Acoustics Lab, MoE Key Lab of Artificial Intelligence,Department of Computer Science and Engineering,Shanghai"],"affiliations":[{"raw_affiliation_string":"AI Institute, Shanghai Jiao Tong University,Auditory Cognition and Computational Acoustics Lab, MoE Key Lab of Artificial Intelligence,Department of Computer Science and Engineering,Shanghai","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100341993","display_name":"Yanmin Qian","orcid":"https://orcid.org/0000-0002-0314-3790"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanmin Qian","raw_affiliation_strings":["AI Institute, Shanghai Jiao Tong University,Auditory Cognition and Computational Acoustics Lab, MoE Key Lab of Artificial Intelligence,Department of Computer Science and Engineering,Shanghai"],"affiliations":[{"raw_affiliation_string":"AI Institute, Shanghai Jiao Tong University,Auditory Cognition and Computational Acoustics Lab, MoE Key Lab of Artificial Intelligence,Department of Computer Science and Engineering,Shanghai","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101416769"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21970782,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"701","last_page":"705"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9958999752998352,"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":0.9958999752998352,"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":0.9761999845504761,"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/adversarial-system","display_name":"Adversarial system","score":0.8376995921134949},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8182954788208008},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.7965583801269531},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5814662575721741},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5489414930343628},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5480794906616211},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5466892123222351},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.45765626430511475},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.45687687397003174},{"id":"https://openalex.org/keywords/speaker-verification","display_name":"Speaker verification","score":0.42384597659111023},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4215736985206604},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3356885015964508},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.08490270376205444},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0603581964969635}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8376995921134949},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8182954788208008},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.7965583801269531},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5814662575721741},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5489414930343628},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5480794906616211},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5466892123222351},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.45765626430511475},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.45687687397003174},{"id":"https://openalex.org/C2982762665","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker verification","level":3,"score":0.42384597659111023},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4215736985206604},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3356885015964508},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08490270376205444},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0603581964969635},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","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/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscslp63861.2024.10800283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscslp63861.2024.10800283","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 14th International Symposium on Chinese Spoken Language Processing (ISCSLP)","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":32,"referenced_works":["https://openalex.org/W1006777433","https://openalex.org/W2121812409","https://openalex.org/W2360384684","https://openalex.org/W2747238065","https://openalex.org/W2748488820","https://openalex.org/W2794506738","https://openalex.org/W2799508475","https://openalex.org/W2801581493","https://openalex.org/W2888968865","https://openalex.org/W2889519245","https://openalex.org/W2890964092","https://openalex.org/W2936780106","https://openalex.org/W2962788262","https://openalex.org/W2962788625","https://openalex.org/W2963450999","https://openalex.org/W2972369255","https://openalex.org/W2972414786","https://openalex.org/W2973049979","https://openalex.org/W2981087920","https://openalex.org/W3010925296","https://openalex.org/W3015213852","https://openalex.org/W3015598461","https://openalex.org/W3024869864","https://openalex.org/W3095862185","https://openalex.org/W3160646455","https://openalex.org/W6631362777","https://openalex.org/W6637618735","https://openalex.org/W6639480849","https://openalex.org/W6769178842","https://openalex.org/W6774314701","https://openalex.org/W6779230768","https://openalex.org/W6781368565"],"related_works":["https://openalex.org/W66821593","https://openalex.org/W1521299571","https://openalex.org/W3141593045","https://openalex.org/W204267554","https://openalex.org/W3211393740","https://openalex.org/W3208049411","https://openalex.org/W2134501921","https://openalex.org/W2886606195","https://openalex.org/W4252590334","https://openalex.org/W2543777506"],"abstract_inverted_index":{"Adapting":[0],"an":[1],"existing":[2],"well-trained":[3],"system":[4,109,118,146],"to":[5,99],"a":[6,14,60],"new":[7],"domain":[8,33,38,45,90,105,177],"using":[9],"only":[10],"unlabeled":[11],"data":[12,100,106],"is":[13,82,96],"highly":[15,83],"sought-after":[16],"yet":[17],"challenging":[18],"task":[19],"for":[20],"speaker":[21],"verification":[22],"in":[23,56],"real-world":[24],"scenarios.":[25],"In":[26],"this":[27],"paper,":[28],"we":[29,58,120],"study":[30],"two":[31],"different":[32],"adaptation":[34,39,46,54,72],"methods,":[35],"the":[36,42,50,64,68,78,86,93,122,144,157,169],"adversarial":[37],"(ADA)":[40],"and":[41,70,126,133,161,172],"self-supervised":[43],"learning-based":[44],"(SSDA).":[47],"To":[48,115],"facilitate":[49],"deployment":[51],"of":[52,63,66,88],"unsupervised":[53],"methods":[55],"applications,":[57],"conduct":[59],"detailed":[61],"analysis":[62],"characteristics":[65],"both":[67,139],"ADA":[69,94,113,125,132],"SSDA":[71,79,108,134],"strategies.":[73],"Our":[74,128],"findings":[75],"indicate":[76],"that":[77,131],"strategy's":[80],"performance":[81,110],"influenced":[84],"by":[85],"amount":[87],"target":[89,104],"data,":[91],"whereas":[92],"strategy":[95],"relatively":[97],"insensitive":[98],"quantity.":[101],"Furthermore,":[102],"augmenting":[103],"enhances":[107],"but":[111],"diminishes":[112],"performance.":[114],"further":[116],"enhance":[117],"performance,":[119],"explore":[121],"complementarity":[123],"between":[124],"SSDA.":[127],"results":[129],"demonstrate":[130],"complement":[135],"each":[136],"other.":[137],"When":[138],"strategies":[140],"are":[141],"applied":[142],"jointly,":[143],"best":[145],"achieves":[147],"over":[148,162],"20.0%":[149],"relative":[150,164],"Equal":[151],"Error":[152],"Rate":[153],"(EER)":[154],"improvement":[155,167],"on":[156,168],"Cnceleb":[158],"evaluation":[159,174],"set":[160,175],"35.0%":[163],"average":[165],"EER":[166],"SRE16":[170],"Cantonese":[171],"Tagalog":[173],"under":[176],"mismatched":[178],"conditions.":[179]},"counts_by_year":[],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}
