{"id":"https://openalex.org/W3011185790","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023165","title":"A Study on Angular Based Embedding Learning for Text-independent Speaker Verification","display_name":"A Study on Angular Based Embedding Learning for Text-independent Speaker Verification","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3011185790","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023165","mag":"3011185790"},"language":"en","primary_location":{"id":"doi:10.1109/apsipaasc47483.2019.9023165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023165","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5100370053","display_name":"Zhiyong Chen","orcid":"https://orcid.org/0000-0002-2033-4249"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Chen","raw_affiliation_strings":["Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080541575","display_name":"Zongze Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongze Ren","raw_affiliation_strings":["Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084521046","display_name":"Shugong Xu","orcid":"https://orcid.org/0000-0003-1905-6269"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shugong Xu","raw_affiliation_strings":["Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"445","last_page":"449"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994999766349792,"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":0.9991999864578247,"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/discriminative-model","display_name":"Discriminative model","score":0.7828180193901062},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.7794917225837708},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7453277707099915},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7285838723182678},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5496264696121216},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5122036337852478},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4997081756591797},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4908464550971985},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.44905686378479004},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4295247197151184},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3516860604286194},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.26339489221572876}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7828180193901062},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.7794917225837708},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7453277707099915},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7285838723182678},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5496264696121216},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5122036337852478},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4997081756591797},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4908464550971985},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.44905686378479004},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4295247197151184},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3516860604286194},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26339489221572876},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipaasc47483.2019.9023165","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023165","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7599999904632568,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2041823554","https://openalex.org/W2046056978","https://openalex.org/W2096733369","https://openalex.org/W2121812409","https://openalex.org/W2136879537","https://openalex.org/W2150769028","https://openalex.org/W2302255633","https://openalex.org/W2395750323","https://openalex.org/W2612434969","https://openalex.org/W2726515241","https://openalex.org/W2747238065","https://openalex.org/W2748488820","https://openalex.org/W2784163702","https://openalex.org/W2802488037","https://openalex.org/W2808631503","https://openalex.org/W2888968865","https://openalex.org/W2889045432","https://openalex.org/W2889151164","https://openalex.org/W2890964092","https://openalex.org/W2955488837","https://openalex.org/W2961224374","https://openalex.org/W2962788625","https://openalex.org/W2962898354","https://openalex.org/W2963224870","https://openalex.org/W2963466847","https://openalex.org/W2963902346","https://openalex.org/W2969985801","https://openalex.org/W2972909277","https://openalex.org/W2972986505","https://openalex.org/W3103152812","https://openalex.org/W4240805545","https://openalex.org/W6698183232","https://openalex.org/W6748010250","https://openalex.org/W6748257384","https://openalex.org/W6751593755","https://openalex.org/W6765548407"],"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/W4287113729","https://openalex.org/W3173314472","https://openalex.org/W3103152812","https://openalex.org/W2162582511"],"abstract_inverted_index":{"Learning":[0],"a":[1,93,108],"good":[2],"speaker":[3,10,68],"embedding":[4,33,55,84,110],"is":[5,78],"important":[6,79],"for":[7,27,95,106],"many":[8],"automatic":[9],"recognition":[11,69],"tasks,":[12],"including":[13],"verification,":[14],"identification":[15],"and":[16,44,61,136],"diarization.":[17],"The":[18],"embeddings":[19],"learned":[20],"by":[21,40],"softmax":[22,147],"are":[23],"not":[24],"discriminative":[25,109],"enough":[26],"open-set":[28],"verification":[29],"tasks.":[30],"Angular":[31],"based":[32,83,97],"learning":[34,56,107],"target":[35],"can":[36],"achieve":[37,124],"such":[38],"discriminativeness":[39],"optimizing":[41],"angular":[42,53,82,96],"distance":[43],"adding":[45],"margin":[46,54],"penalty.":[47],"We":[48,99],"apply":[49],"several":[50,116],"different":[51],"popular":[52],"strategies":[57],"in":[58],"this":[59],"work":[60],"explicitly":[62],"compare":[63],"their":[64],"performance":[65],"on":[66,112,131,139],"Voxceleb":[67],"dataset.":[70],"Observing":[71],"the":[72,101],"fact":[73],"that":[74],"encouraging":[75],"inter-class":[76,90],"separability":[77],"when":[80],"applying":[81],"learning,":[85],"we":[86,121],"propose":[87],"an":[88,125],"exclusive":[89],"regularization":[91],"as":[92],"complement":[94],"loss.":[98],"verify":[100],"effectiveness":[102],"of":[103],"these":[104],"methods":[105,119],"space":[111],"ASV":[113],"task":[114],"with":[115,128,145],"experiments.":[117],"These":[118],"together,":[120],"manage":[122],"to":[123],"impressive":[126],"result":[127],"16.5%":[129],"improvement":[130,138],"equal":[132],"error":[133],"rate":[134],"(EER)":[135],"18.2%":[137],"minimum":[140],"detection":[141],"cost":[142],"function":[143],"comparing":[144],"baseline":[146],"systems.":[148]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
