{"id":"https://openalex.org/W2963785573","doi":"https://doi.org/10.1109/asru.2017.8268995","title":"Comparison of multiple features and modeling methods for text-dependent speaker verification","display_name":"Comparison of multiple features and modeling methods for text-dependent speaker verification","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2963785573","doi":"https://doi.org/10.1109/asru.2017.8268995","mag":"2963785573"},"language":"en","primary_location":{"id":"doi:10.1109/asru.2017.8268995","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru.2017.8268995","pdf_url":null,"source":{"id":"https://openalex.org/S4306498158","display_name":"2017 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":"2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","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/A5100695128","display_name":"Yi Liu","orcid":"https://orcid.org/0000-0001-9993-0731"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Liu","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049944728","display_name":"Liang He","orcid":"https://orcid.org/0000-0003-4076-7479"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang He","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100571324","display_name":"Yao Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Tian","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006960202","display_name":"Zhuzi Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuzi Chen","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100409741","display_name":"Jia Liu","orcid":"https://orcid.org/0000-0003-0383-0934"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Liu","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015797517","display_name":"Michael T. Johnson","orcid":"https://orcid.org/0000-0001-5424-4877"},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael T. Johnson","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY","institution_ids":["https://openalex.org/I143302722"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"629","last_page":"636"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9950000047683716,"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":0.9941999912261963,"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/hidden-markov-model","display_name":"Hidden Markov model","score":0.8087819218635559},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.778512716293335},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.7260296940803528},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6893037557601929},{"id":"https://openalex.org/keywords/viterbi-algorithm","display_name":"Viterbi algorithm","score":0.6712735891342163},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.6027241945266724},{"id":"https://openalex.org/keywords/speaker-verification","display_name":"Speaker verification","score":0.5928429365158081},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.546027660369873},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5420817136764526},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.529959499835968},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4736156165599823},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4377455711364746},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4140816330909729},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.36457738280296326},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07724705338478088}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8087819218635559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.778512716293335},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7260296940803528},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6893037557601929},{"id":"https://openalex.org/C60582962","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Viterbi algorithm","level":3,"score":0.6712735891342163},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.6027241945266724},{"id":"https://openalex.org/C2982762665","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker verification","level":3,"score":0.5928429365158081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.546027660369873},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5420817136764526},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.529959499835968},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4736156165599823},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4377455711364746},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4140816330909729},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36457738280296326},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07724705338478088},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asru.2017.8268995","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru.2017.8268995","pdf_url":null,"source":{"id":"https://openalex.org/S4306498158","display_name":"2017 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":"2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W123007118","https://openalex.org/W1006777433","https://openalex.org/W1494198834","https://openalex.org/W1555845489","https://openalex.org/W1996512145","https://openalex.org/W2039057510","https://openalex.org/W2041823554","https://openalex.org/W2114925438","https://openalex.org/W2125838338","https://openalex.org/W2150769028","https://openalex.org/W2154278880","https://openalex.org/W2333871989","https://openalex.org/W2339819627","https://openalex.org/W2398971481","https://openalex.org/W2400873347","https://openalex.org/W2407857848","https://openalex.org/W2484386994","https://openalex.org/W2508150396","https://openalex.org/W2508175215","https://openalex.org/W2510625446","https://openalex.org/W2514080268","https://openalex.org/W2514700786","https://openalex.org/W2516985725","https://openalex.org/W2578080057","https://openalex.org/W2584329820","https://openalex.org/W2587150483","https://openalex.org/W2606778926","https://openalex.org/W2612122134","https://openalex.org/W2612434969","https://openalex.org/W2640876020","https://openalex.org/W2962832278","https://openalex.org/W2963565199","https://openalex.org/W6605010638","https://openalex.org/W6712618806","https://openalex.org/W6712744388","https://openalex.org/W6732884072","https://openalex.org/W6737575990"],"related_works":["https://openalex.org/W2734857650","https://openalex.org/W1534614538","https://openalex.org/W150593575","https://openalex.org/W2398196429","https://openalex.org/W292968312","https://openalex.org/W3022377205","https://openalex.org/W3201363892","https://openalex.org/W2936847140","https://openalex.org/W2182106261","https://openalex.org/W2339853598","https://openalex.org/W2253824031","https://openalex.org/W2972924883","https://openalex.org/W3120856754","https://openalex.org/W3094350817","https://openalex.org/W3163929126","https://openalex.org/W2591460962","https://openalex.org/W150587182","https://openalex.org/W2970827607","https://openalex.org/W3198815374","https://openalex.org/W2916058012"],"abstract_inverted_index":{"Text-dependent":[0],"speaker":[1,8,21,165],"verification":[2],"is":[3,44,50],"becoming":[4],"popular":[5],"in":[6,30,98,124],"the":[7,12,51,56,77,85,99,115,118,125,129,142,149,173],"recognition":[9],"society.":[10],"However,":[11],"conventional":[13],"i-vector":[14],"framework":[15],"which":[16,48],"has":[17],"been":[18],"successful":[19],"for":[20,163],"identification":[22],"and":[23,62,72,92,133],"other":[24],"similar":[25],"tasks":[26],"works":[27],"relatively":[28],"poorly":[29],"this":[31,65],"task.":[32],"Researchers":[33],"have":[34],"proposed":[35],"several":[36],"new":[37],"methods":[38,71],"to":[39,148],"improve":[40],"performance,":[41],"but":[42],"it":[43],"still":[45],"unclear":[46],"that":[47,156],"model":[49],"best":[52],"choice,":[53],"especially":[54],"when":[55],"pass-phrases":[57],"are":[58,95,105,135],"prompted":[59],"during":[60],"enrollment":[61],"test.":[63],"In":[64,128,139],"paper,":[66],"we":[67,153],"introduce":[68],"four":[69],"modeling":[70,114,120],"compare":[73],"their":[74],"performance":[75],"on":[76,172,178],"newly":[78],"published":[79],"RedDots":[80],"dataset.":[81],"To":[82],"further":[83],"explore":[84],"influence":[86],"of":[87],"different":[88],"frame":[89],"alignments,":[90],"Viterbi":[91],"forward-backward":[93,143],"algorithms":[94],"both":[96,140],"used":[97],"HMM-based":[100,119],"models.":[101],"Several":[102],"bottleneck":[103,159],"features":[104,160],"also":[106,154],"investigated.":[107],"Our":[108],"experiments":[109],"show":[110],"that,":[111],"by":[112],"explicitly":[113],"lexical":[116],"content,":[117],"achieves":[121],"good":[122],"results":[123],"fixed-phrase":[126],"condition.":[127],"prompted-phrase":[130],"condition,":[131],"GMM-HMM":[132],"i-vector/HMM":[134,150],"not":[136,169],"as":[137],"successful.":[138],"conditions,":[141],"algorithm":[144],"brings":[145],"more":[146],"benefits":[147],"system.":[151],"Additionally,":[152],"find":[155],"even":[157],"though":[158],"perform":[161],"well":[162],"text-independent":[164],"verification,":[166],"they":[167],"do":[168],"outperform":[170],"MFCCs":[171],"most":[174],"challenging":[175],"Imposter-Correct":[176],"trials":[177],"RedDots.":[179]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}