{"id":"https://openalex.org/W2999547272","doi":"https://doi.org/10.1109/asru46091.2019.9003826","title":"CNN with Phonetic Attention for Text-Independent Speaker Verification","display_name":"CNN with Phonetic Attention for Text-Independent Speaker Verification","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W2999547272","doi":"https://doi.org/10.1109/asru46091.2019.9003826","mag":"2999547272"},"language":"en","primary_location":{"id":"doi:10.1109/asru46091.2019.9003826","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru46091.2019.9003826","pdf_url":null,"source":{"id":"https://openalex.org/S4306498489","display_name":"2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","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/A5103218426","display_name":"Tianyan Zhou","orcid":"https://orcid.org/0000-0003-3238-2982"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tianyan Zhou","raw_affiliation_strings":["Microsoft Corporation, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100702071","display_name":"Yong Zhao","orcid":"https://orcid.org/0000-0003-2644-952X"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yong Zhao","raw_affiliation_strings":["Microsoft Corporation, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365053","display_name":"Jinyu Li","orcid":"https://orcid.org/0000-0002-1089-9748"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinyu Li","raw_affiliation_strings":["Microsoft Corporation, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101928537","display_name":"Yifan Gong","orcid":"https://orcid.org/0000-0002-3912-097X"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yifan Gong","raw_affiliation_strings":["Microsoft Corporation, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101674460","display_name":"Jian Wu","orcid":"https://orcid.org/0000-0002-3101-7011"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jian Wu","raw_affiliation_strings":["Microsoft Corporation, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103218426"],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":6.1607,"has_fulltext":false,"cited_by_count":64,"citation_normalized_percentile":{"value":0.97100371,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"718","last_page":"725"},"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":0.9987000226974487,"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":0.8377729654312134},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.694668710231781},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6459567546844482},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5913773775100708},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5846737027168274},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5607278943061829},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5534359812736511},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.376193106174469},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3669518828392029}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8377729654312134},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.694668710231781},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6459567546844482},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5913773775100708},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5846737027168274},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5607278943061829},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5534359812736511},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.376193106174469},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3669518828392029},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asru46091.2019.9003826","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru46091.2019.9003826","pdf_url":null,"source":{"id":"https://openalex.org/S4306498489","display_name":"2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W2004497042","https://openalex.org/W2039057510","https://openalex.org/W2046056978","https://openalex.org/W2070176749","https://openalex.org/W2078169166","https://openalex.org/W2096733369","https://openalex.org/W2114925438","https://openalex.org/W2121812409","https://openalex.org/W2133564696","https://openalex.org/W2138621090","https://openalex.org/W2150769028","https://openalex.org/W2194775991","https://openalex.org/W2290689761","https://openalex.org/W2293634267","https://openalex.org/W2294543795","https://openalex.org/W2395750323","https://openalex.org/W2401594978","https://openalex.org/W2584329820","https://openalex.org/W2600537992","https://openalex.org/W2612434969","https://openalex.org/W2726515241","https://openalex.org/W2748488820","https://openalex.org/W2766191375","https://openalex.org/W2794506738","https://openalex.org/W2808631503","https://openalex.org/W2884412522","https://openalex.org/W2889492015","https://openalex.org/W2889519245","https://openalex.org/W2890964092","https://openalex.org/W2916104401","https://openalex.org/W2939248538","https://openalex.org/W2962959915","https://openalex.org/W2963371159","https://openalex.org/W2963466847","https://openalex.org/W2964247977","https://openalex.org/W2964308564","https://openalex.org/W3099206234","https://openalex.org/W3151878189","https://openalex.org/W4234330420","https://openalex.org/W4289750118","https://openalex.org/W4293478066","https://openalex.org/W6660130284","https://openalex.org/W6662018943","https://openalex.org/W6667507107","https://openalex.org/W6679434410","https://openalex.org/W6696345733","https://openalex.org/W6696912008","https://openalex.org/W6742911084","https://openalex.org/W6750372021","https://openalex.org/W6753575415","https://openalex.org/W6754496211"],"related_works":["https://openalex.org/W2514274290","https://openalex.org/W2729514902","https://openalex.org/W2024160000","https://openalex.org/W2773500201","https://openalex.org/W2061273563","https://openalex.org/W4319301798","https://openalex.org/W4287995534","https://openalex.org/W2743258233","https://openalex.org/W2970216048","https://openalex.org/W2043075591"],"abstract_inverted_index":{"Text-independent":[0],"speaker":[1,25],"verification":[2],"imposes":[3],"no":[4],"constraints":[5],"on":[6,151],"the":[7,30,34,46,59,76,81,84,92,99,110,114,122,128,135,148,152,161],"spoken":[8,117],"content":[9,118],"and":[10,72,119,140],"usually":[11],"needs":[12],"long":[13],"observations":[14],"to":[15,98,108,146],"make":[16],"reliable":[17],"prediction.":[18],"In":[19,54,87],"this":[20],"paper,":[21],"we":[22],"propose":[23],"two":[24],"embedding":[26],"approaches":[27],"by":[28,64,163],"integrating":[29],"phonetic":[31,56,60,89,93,136],"information":[32],"into":[33,68],"attention-based":[35],"residual":[36],"convolutional":[37],"neural":[38],"network":[39,67],"(CNN).":[40],"Phonetic":[41],"features":[42,61,79,94],"are":[43,62,95,143],"extracted":[44],"from":[45],"bottleneck":[47],"layer":[48,102],"of":[49,83,116],"a":[50,65,104],"pretrained":[51],"acoustic":[52,78],"model.":[53],"implicit":[55],"attention":[57,90,111,120,139],"(IPA),":[58],"projected":[63],"transformation":[66],"multi-channel":[69],"feature":[70],"maps,":[71],"then":[73],"combined":[74],"with":[75],"raw":[77],"as":[80],"input":[82],"CNN":[85,107],"network.":[86],"explicit":[88],"(EPA),":[91],"directly":[96],"connected":[97],"attentive":[100],"pooling":[101],"through":[103],"separate":[105],"1-dim":[106],"generate":[109],"weights.":[112],"With":[113],"incorporation":[115],"mechanism,":[121],"system":[123,158],"can":[124],"not":[125],"only":[126],"distill":[127],"speaker-discriminant":[129],"frames":[130],"but":[131],"also":[132],"actively":[133],"normalize":[134],"variations.":[137],"Multi-head":[138],"discriminative":[141],"objectives":[142],"further":[144],"studied":[145],"improve":[147],"system.":[149],"Experiments":[150],"VoxCeleb":[153],"corpus":[154],"show":[155],"our":[156],"proposed":[157],"could":[159],"outperform":[160],"state-of-the-art":[162],"around":[164],"43%":[165],"relative.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":22},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
