{"id":"https://openalex.org/W4406858911","doi":"https://doi.org/10.1109/apsipaasc63619.2025.10849026","title":"Semi-Supervised Far-Field Speaker Verification with Distance Metric Domain Adaptation","display_name":"Semi-Supervised Far-Field Speaker Verification with Distance Metric Domain Adaptation","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406858911","doi":"https://doi.org/10.1109/apsipaasc63619.2025.10849026"},"language":"en","primary_location":{"id":"doi:10.1109/apsipaasc63619.2025.10849026","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc63619.2025.10849026","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5100452721","display_name":"Han Wang","orcid":"https://orcid.org/0000-0002-6970-9806"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Han Wang","raw_affiliation_strings":["Donghua University,School of Information Science and Technology,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Donghua University,School of Information Science and Technology,Shanghai,China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056865774","display_name":"Mingrui He","orcid":"https://orcid.org/0009-0006-0378-5570"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingrui He","raw_affiliation_strings":["Donghua University,School of Information Science and Technology,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Donghua University,School of Information Science and Technology,Shanghai,China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100709816","display_name":"Mingjun Zhang","orcid":"https://orcid.org/0000-0002-0641-1877"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingjun Zhang","raw_affiliation_strings":["Donghua University,School of Information Science and Technology,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Donghua University,School of Information Science and Technology,Shanghai,China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045048913","display_name":"Longting Xu","orcid":"https://orcid.org/0000-0002-2329-895X"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longting Xu","raw_affiliation_strings":["Donghua University,School of Information Science and Technology,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Donghua University,School of Information Science and Technology,Shanghai,China","institution_ids":["https://openalex.org/I181326427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100452721"],"corresponding_institution_ids":["https://openalex.org/I181326427"],"apc_list":null,"apc_paid":null,"fwci":0.3455,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.60767478,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9983000159263611,"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":0.9983000159263611,"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":0.9948999881744385,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9136000275611877,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.6983461380004883},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6957256197929382},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6345260739326477},{"id":"https://openalex.org/keywords/near-and-far-field","display_name":"Near and far field","score":0.5708010196685791},{"id":"https://openalex.org/keywords/speaker-verification","display_name":"Speaker verification","score":0.5227180123329163},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4876174032688141},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4680841565132141},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4596433639526367},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.42028263211250305},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3979116678237915},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.25794118642807007},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14864706993103027},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12265470623970032},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.06070345640182495}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6983461380004883},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6957256197929382},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6345260739326477},{"id":"https://openalex.org/C25227671","wikidata":"https://www.wikidata.org/wiki/Q13405516","display_name":"Near and far field","level":2,"score":0.5708010196685791},{"id":"https://openalex.org/C2982762665","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker verification","level":3,"score":0.5227180123329163},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4876174032688141},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4680841565132141},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4596433639526367},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.42028263211250305},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3979116678237915},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.25794118642807007},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14864706993103027},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12265470623970032},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.06070345640182495},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipaasc63619.2025.10849026","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc63619.2025.10849026","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320323710","display_name":"Donghua University","ror":"https://ror.org/035psfh38"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1995996823","https://openalex.org/W2114925438","https://openalex.org/W2121750345","https://openalex.org/W2121947440","https://openalex.org/W2131681506","https://openalex.org/W2150769028","https://openalex.org/W2164998314","https://openalex.org/W2360384684","https://openalex.org/W2528237000","https://openalex.org/W2726515241","https://openalex.org/W2746742816","https://openalex.org/W2784163702","https://openalex.org/W2801581493","https://openalex.org/W2890964092","https://openalex.org/W2897249806","https://openalex.org/W2972315886","https://openalex.org/W2972697221","https://openalex.org/W2984353870","https://openalex.org/W3137249133","https://openalex.org/W3163421828","https://openalex.org/W3198104675","https://openalex.org/W4213444572","https://openalex.org/W4224925560","https://openalex.org/W4224931675","https://openalex.org/W4306867198","https://openalex.org/W4306867253","https://openalex.org/W4372260593","https://openalex.org/W4372340947","https://openalex.org/W4388821404","https://openalex.org/W4392904642","https://openalex.org/W6682346614","https://openalex.org/W6757817989","https://openalex.org/W6779961489"],"related_works":["https://openalex.org/W2997567050","https://openalex.org/W2376224659","https://openalex.org/W2169064893","https://openalex.org/W32484671","https://openalex.org/W4294437891","https://openalex.org/W4394775207","https://openalex.org/W2886606195","https://openalex.org/W3120856754","https://openalex.org/W2747741332","https://openalex.org/W4306867253"],"abstract_inverted_index":{"Achieving":[0],"high":[1],"performance":[2],"in":[3,109],"far-field":[4,39],"speaker":[5,33],"verification":[6],"is":[7,23,160],"challenging":[8],"due":[9],"to":[10,24,63,114,121],"the":[11,56,96,110,132,135,142,154,164,171,180],"scarcity":[12],"of":[13,17,37,50,99,134,156],"data":[14],"and":[15,41,55,80,92,141,146],"prevalence":[16],"low-quality":[18],"labels.":[19],"A":[20,30],"common":[21],"approach":[22,123],"use":[25],"a":[26,73,84],"semi-supervised":[27,65],"learning":[28,66],"framework.":[29,67],"pre-trained":[31],"near-field":[32],"model":[34],"extracts":[35],"embeddings":[36],"unlabeled":[38],"speakers,":[40],"clustering":[42,54],"methods":[43],"generate":[44],"pseudo-labels":[45],"for":[46,88],"fine-tuning.":[47],"The":[48],"accuracy":[49,155],"pseudo-label":[51],"generation":[52],"through":[53],"domain":[57,107,116,127,176],"adaptation":[58,117,128],"during":[59,118,179],"fine-tuning":[60,181],"are":[61],"critical":[62],"this":[64,69,122],"In":[68],"paper,":[70],"we":[71],"propose":[72],"method":[74,173],"that":[75,153],"combines":[76],"Uniform":[77],"Manifold":[78],"Approximation":[79],"Projection":[81],"(UMAP)":[82],"with":[83],"community":[85,138,167],"detection":[86,139,168],"algorithm":[87],"efficient":[89],"dimensionality":[90,136],"reduction":[91,137],"clustering.":[93,104],"UMAP":[94],"preserves":[95],"structural":[97],"distribution":[98],"high-dimensional":[100],"data,":[101],"facilitating":[102],"better":[103],"We":[105,130],"conduct":[106],"alignment":[108],"distance":[111,125],"metric":[112,126],"space":[113],"achieve":[115],"fine-tuning,":[119],"referring":[120],"as":[124],"(DMDA).":[129],"evaluate":[131],"effectiveness":[133],"agorithm":[140],"on":[143],"VoxCeleb":[144],"(pre-trained)":[145],"FFSVC":[147],"(fine-tuned)":[148],"datasets.":[149],"Experimental":[150],"results":[151],"demonstrate":[152],"generating":[157],"pseudo":[158],"labels":[159],"improved":[161],"by":[162],"using":[163],"reduced":[165],"dimensional":[166],"algorithm.":[169],"Additionally,":[170],"DMDA":[172],"effectively":[174],"reduces":[175],"mismatch":[177],"issues":[178],"process.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2025-10-10T00:00:00"}