{"id":"https://openalex.org/W314868406","doi":"https://doi.org/10.21437/interspeech.2006-173","title":"A novel framework of text-independent speaker verification based on utterance transform and iterative cohort modeling","display_name":"A novel framework of text-independent speaker verification based on utterance transform and iterative cohort modeling","publication_year":2006,"publication_date":"2006-09-17","ids":{"openalex":"https://openalex.org/W314868406","doi":"https://doi.org/10.21437/interspeech.2006-173","mag":"314868406"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2006-173","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2006-173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2006","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/A5100773530","display_name":"Ming Liu","orcid":"https://orcid.org/0009-0001-9684-0009"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming Liu","raw_affiliation_strings":["University of Illinois at Urbana Champaign"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana Champaign","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112466665","display_name":"Huazhong Ning","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huazhong Ning","raw_affiliation_strings":["University of Illinois at Urbana Champaign"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana Champaign","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101457342","display_name":"Thomas S. Huang","orcid":"https://orcid.org/0000-0001-8474-5859"},"institutions":[{"id":"https://openalex.org/I4400573203","display_name":"Nature Inspires Creativity Engineers Lab","ror":"https://ror.org/02bczqy30","country_code":null,"type":"facility","lineage":["https://openalex.org/I201841394","https://openalex.org/I4400573203"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Thomas S. Huang","raw_affiliation_strings":["Coordinated Science Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Coordinated Science Lab","institution_ids":["https://openalex.org/I4400573203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058849717","display_name":"Zhengyou Zhang","orcid":"https://orcid.org/0000-0002-6606-2525"},"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"]},{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB","US"],"is_corresponding":false,"raw_author_name":"Zhengyou Zhang","raw_affiliation_strings":["Microsoft , USA "],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft , USA ","institution_ids":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"paper 2034","last_page":"Tue1CaP.7"},"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":0.996999979019165,"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":0.9890000224113464,"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/utterance","display_name":"Utterance","score":0.7502610683441162},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.7099965810775757},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6250519752502441},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5901443362236023},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.44977590441703796},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.44890281558036804},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4210154414176941},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34794941544532776}],"concepts":[{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.7502610683441162},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.7099965810775757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6250519752502441},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5901443362236023},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.44977590441703796},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.44890281558036804},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4210154414176941},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34794941544532776},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.21437/interspeech.2006-173","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2006-173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2006","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.150.1954","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.150.1954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/~zhang/Papers/Interspeech06-ti-sv.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.332.4434","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.332.4434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ifp.illinois.edu/~hning2/papers/mingliu_icslp06.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W46639971","https://openalex.org/W65288015","https://openalex.org/W86630384","https://openalex.org/W2002123483","https://openalex.org/W2041823554","https://openalex.org/W2049633694","https://openalex.org/W2078953162","https://openalex.org/W2100969003","https://openalex.org/W2113755283","https://openalex.org/W2166473218","https://openalex.org/W2397634864"],"related_works":["https://openalex.org/W2158491338","https://openalex.org/W2807901368","https://openalex.org/W2133733652","https://openalex.org/W2072658171","https://openalex.org/W2606392311","https://openalex.org/W2320042380","https://openalex.org/W4385956668","https://openalex.org/W2900895161","https://openalex.org/W4380838366","https://openalex.org/W2539884462"],"abstract_inverted_index":{"A":[0],"novel":[1,205],"framework":[2,10,25,103,217],"for":[3,161],"text-independent":[4],"speaker":[5,234],"verification":[6],"is":[7,11,45,62,116,159],"proposed.":[8],"The":[9,21,55,71,101,125],"based":[12],"on":[13,73,223],"a":[14,28,37,49],"new":[15,82,102],"interpretation":[16],"of":[17,80,123,129,142,155,187,204],"Universal":[18],"Background":[19],"Model.":[20],"UBM":[22],"in":[23,51,58,110,119,171],"our":[24],"actually":[26],"defines":[27],"transform":[29],"which":[30,115,213],"maps":[31],"the":[32,78,85,89,107,111,120,140,152,162,178,184,188,198,202,210,216,220,224,228],"variable":[33],"length":[34],"observation":[35],"into":[36,48],"fixed":[38],"dimensional":[39],"supervector(supervector":[40],"space).":[41],"Each":[42],"speech":[43],"utterance":[44,236],"then":[46],"mapped":[47],"point":[50],"this":[52,59,81],"supervector":[53,225],"space.":[54],"similarity":[56,221],"measure":[57,222],"vector":[60],"space":[61,226],"progressively":[63,218],"refined":[64],"via":[65],"an":[66],"iterative":[67,179,229,238],"cohort":[68,180,230,239],"modeling":[69,181],"scheme.":[70],"experiments":[72],"NIST":[74],"2002":[75],"corpus":[76],"show":[77],"effectiveness":[79],"framework.":[83],"Overall":[84],"EER":[86,126,141],"drops":[87,145],"from":[88],"baseline":[90,143,172],"system(with":[91],"T-Norm)":[92,99],"9.21":[93],"%":[94,137,147,170],"to":[95,139,168],"final":[96,112,130,163,189],"improved":[97,164],"system(without":[98],"8.07%.":[100],"can":[104],"effectively":[105,182],"reduce":[106,183],"data":[108,185],"dependence":[109,186],"output":[113],"score":[114],"clearly":[117,207],"indicated":[118],"second":[121],"sets":[122],"experiments.":[124],"after":[127,149,157],"T-Norm":[128,158,193],"system":[131,144,165,199],"marginally":[132],"increases":[133,208],"by":[134],"relatively":[135,148],"1.73":[136],"compared":[138,167],"16.12":[146],"T-Norm.":[150],"Also,":[151,201],"relative":[153],"improvement":[154],"DCF":[156],"marginal":[160],"(2.47%)":[166],"33.68":[169],"system.":[173],"It":[174],"clear":[175],"shows":[176],"that":[177,192,215],"scores,":[190],"so":[191],"will":[194],"not":[195],"further":[196],"improve":[197],"performance.":[200],"performance":[203],"frame":[206],"as":[209],"iteration":[211],"grows":[212],"suggest":[214],"refine":[219],"with":[227],"modeling.":[231,240],"Index":[232],"Terms:":[233],"verification,":[235],"transform,":[237]},"counts_by_year":[{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
