{"id":"https://openalex.org/W6946262434","doi":"https://doi.org/10.26190/unsworks/19497","title":"Robust speaker verification system","display_name":"Robust speaker verification system","publication_year":2022,"publication_date":"2022-03-22","ids":{"openalex":"https://openalex.org/W6946262434","doi":"https://doi.org/10.26190/unsworks/19497"},"language":"en","primary_location":{"id":"pmh:oai:unsworks.unsw.edu.au:1959.4/42796","is_oa":false,"landing_page_url":"http://handle.unsw.edu.au/1959.4/42796","pdf_url":null,"source":{"id":"https://openalex.org/S4377196481","display_name":"UNSWorks (UNSW Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I31746571","host_organization_name":"UNSW Sydney","host_organization_lineage":["https://openalex.org/I31746571"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},"type":"dissertation","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.26190/unsworks/19497","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Nosratighods, Mohaddeseh","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Nosratighods, Mohaddeseh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.8959000110626221,"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":0.8959000110626221,"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":0.03099999949336052,"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/T10057","display_name":"Face and Expression Recognition","score":0.009200000204145908,"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/speaker-recognition","display_name":"Speaker recognition","score":0.6901000142097473},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6459000110626221},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.6100000143051147},{"id":"https://openalex.org/keywords/microphone","display_name":"Microphone","score":0.5677000284194946},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.5397999882698059},{"id":"https://openalex.org/keywords/timit","display_name":"TIMIT","score":0.5358999967575073},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.5184999704360962},{"id":"https://openalex.org/keywords/telephony","display_name":"Telephony","score":0.5037000179290771},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43630000948905945},{"id":"https://openalex.org/keywords/speaker-verification","display_name":"Speaker verification","score":0.41339999437332153}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7620000243186951},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7554000020027161},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.6901000142097473},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6459000110626221},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.6100000143051147},{"id":"https://openalex.org/C2778263558","wikidata":"https://www.wikidata.org/wiki/Q46384","display_name":"Microphone","level":3,"score":0.5677000284194946},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.5397999882698059},{"id":"https://openalex.org/C2778724510","wikidata":"https://www.wikidata.org/wiki/Q7670405","display_name":"TIMIT","level":3,"score":0.5358999967575073},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.5184999704360962},{"id":"https://openalex.org/C195358072","wikidata":"https://www.wikidata.org/wiki/Q944584","display_name":"Telephony","level":2,"score":0.5037000179290771},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43630000948905945},{"id":"https://openalex.org/C2982762665","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker verification","level":3,"score":0.41339999437332153},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.39910000562667847},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3953000009059906},{"id":"https://openalex.org/C148417208","wikidata":"https://www.wikidata.org/wiki/Q4825882","display_name":"Authentication (law)","level":2,"score":0.3917999863624573},{"id":"https://openalex.org/C154504017","wikidata":"https://www.wikidata.org/wiki/Q853614","display_name":"Identifier","level":2,"score":0.391400009393692},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.367000013589859},{"id":"https://openalex.org/C149838564","wikidata":"https://www.wikidata.org/wiki/Q7574248","display_name":"Speaker diarisation","level":3,"score":0.3659000098705292},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.35499998927116394},{"id":"https://openalex.org/C2777185736","wikidata":"https://www.wikidata.org/wiki/Q7265603","display_name":"QUIET","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C59656382","wikidata":"https://www.wikidata.org/wiki/Q191536","display_name":"Conjunction (astronomy)","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34119999408721924},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.31380000710487366},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.3091999888420105},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.26109999418258667},{"id":"https://openalex.org/C204201278","wikidata":"https://www.wikidata.org/wiki/Q1332614","display_name":"Voice activity detection","level":3,"score":0.25690001249313354},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.25619998574256897}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:unsworks.unsw.edu.au:1959.4/42796","is_oa":false,"landing_page_url":"http://handle.unsw.edu.au/1959.4/42796","pdf_url":null,"source":{"id":"https://openalex.org/S4377196481","display_name":"UNSWorks (UNSW Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I31746571","host_organization_name":"UNSW Sydney","host_organization_lineage":["https://openalex.org/I31746571"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},{"id":"pmh:oai:unsworks.library.unsw.edu.au:1959.4/42796","is_oa":false,"landing_page_url":"http://hdl.handle.net/1959.4/42796","pdf_url":null,"source":{"id":"https://openalex.org/S4306401737","display_name":"UNSWorks (University of New South Wales, Sydney, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40053085","host_organization_name":"Australian Defence Force Academy","host_organization_lineage":["https://openalex.org/I40053085"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"http://purl.org/coar/resource_type/c_db06"},{"id":"doi:10.26190/unsworks/19497","is_oa":true,"landing_page_url":"https://doi.org/10.26190/unsworks/19497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Dissertation"}],"best_oa_location":{"id":"doi:10.26190/unsworks/19497","is_oa":true,"landing_page_url":"https://doi.org/10.26190/unsworks/19497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dissertation"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Identity":[0],"verification":[1,27],"or":[2],"biometric":[3,33],"recognition":[4,98,360],"systems":[5,67,120],"play":[6],"an":[7,328],"important":[8],"role":[9],"in":[10,57,121,206,229,265,285,358,397,423],"our":[11],"daily":[12],"lives.":[13],"Applications":[14],"include":[15],"Automatic":[16,63],"Teller":[17],"Machines":[18,304],"(ATM),":[19],"banking":[20],"and":[21,25,51,90,106,130,168,183,188,343,352,407,504],"share":[22],"information":[23,204],"retrieval,":[24],"personal":[26],"for":[28,94,180,320,500],"credit":[29],"cards.":[30],"Among":[31],"the":[32,53,77,116,134,162,177,192,203,212,219,234,241,244,271,277,282,321,338,346,363,374,381,389,411,416,435,445,469,481,501,508,515],"techniques,":[34],"authentication":[35],"of":[36,42,62,84,118,125,140,151,161,191,198,218,243,250,261,324,337,365,373,380,410,440,472,480,491,507],"speakers":[37],"by":[38],"his/her":[39],"voice":[40],"is":[41,52,87,112,148,172,288,306,361,400,420,431,462,485],"great":[43],"importance,":[44],"since":[45],"it":[46],"employs":[47],"a":[48,137,189,207,230,258,457,488],"non-invasive":[49],"approach":[50,296,314,419],"only":[54,157,404,513],"available":[55],"modality":[56],"many":[58],"applications.":[59],"However,the":[60],"performance":[61,179,242,348],"Speaker":[64],"Verification":[65],"(ASV)":[66],"degrades":[68],"significantly":[69],"under":[70,247,349],"adverse":[71],"conditions":[72,185,425],"which":[73,155,201],"cause":[74],"recordings":[75],"from":[76,444],"same":[78,178],"speaker":[79,97,128,199,286,359,391],"to":[80,88,114,175,239,263,297,315,318,332,344,369,388,414,464],"be":[81],"different.The":[82],"objective":[83],"this":[85],"research":[86,111],"investigate":[89],"develop":[91],"robust":[92],"techniques":[93],"performing":[95],"automatic":[96],"over":[99,270],"various":[100,251],"channel":[101,248,289,298,341],"conditions,":[102],"such":[103],"as":[104],"telephony":[105],"recorded":[107],"microphone":[108],"speech.":[109],"This":[110,418],"shown":[113,174],"improve":[115,240,345],"robustness":[117],"ASV":[119,245],"three":[122],"main":[123,283,322],"areas":[124],"feature":[126,135,163,375,436,482],"extraction,":[127],"modelling":[129,287],"score":[131,366,398,441,459],"normalization.":[132],"At":[133],"level,":[136],"new":[138,458],"set":[139],"dynamic":[141],"features,":[142,214],"termed":[143,495],"Delta":[144],"Cepstral":[145],"Energy":[146],"(DCE)":[147],"proposed,":[149],"instead":[150],"traditional":[152],"delta":[153,167],"cepstra,":[154,170],"not":[156,432,448],"greatly":[158],"reduces":[159],"thedimensionality":[160],"vector":[164],"compared":[165],"with":[166,233],"delta-delta":[169],"but":[171],"also":[173],"provide":[176],"matched":[181,387],"testing":[182],"training":[184,351],"on":[186,211,276,301,405,468],"TIMIT":[187],"subset":[190],"NIST":[193,278],"2002":[194],"dataset.":[195,280],"The":[196,253,311],"concept":[197],"entropy,":[200],"conveys":[202],"contained":[205],"speaker's":[208],"speech":[209,383,428],"based":[210,300,467],"extracted":[213],"facilitates":[215],"comparative":[216],"evaluation":[217],"proposed":[220,254,312,401],"methods.":[221],"In":[222],"addition,":[223],"Frequency":[224,236],"Modulation":[225],"features":[226],"are":[227,385,451,498],"combined":[228],"complementary":[231],"manner":[232],"Mel":[235],"CepstralCoefficients":[237],"(MFCCs)":[238],"system":[246,256,273,347,516],"variability":[249,290,364,442],"types.":[252],"fused":[255],"shows":[257],"relative":[259],"reduction":[260],"up":[262],"23%":[264],"Equal":[266],"Error":[267],"Rate":[268],"(EER)":[269],"MFCC-based":[272],"when":[274],"evaluated":[275],"2008":[279],"Currently,":[281],"challenge":[284],"across":[291],"different":[292],"sessions.":[293],"A":[294,393],"recent":[295],"compensation,":[299],"Support":[302],"Vector":[303],"(SVM)":[305],"Nuisance":[307],"Attribute":[308],"Projection":[309],"(NAP).":[310],"multi-component":[313],"NAP,":[316],"attempts":[317],"compensate":[319],"sources":[323],"inter-session":[325],"variations":[326],"through":[327],"additional":[329],"optimization":[330],"criteria,":[331],"allow":[333],"more":[334],"accurate":[335],"estimates":[336],"most":[339],"dominant":[340],"artefacts":[342],"mismatched":[350],"test":[353,382,412],"conditions.":[354],"Another":[355,438],"major":[356],"issue":[357],"that":[362,384,402,447,487,505],"distributions":[367],"due":[368],"incompletely":[370],"modelled":[371],"regions":[372],"space":[376],"can":[377],"produce":[378],"segments":[379,409],"poorly":[386],"claimed":[390],"model.":[392],"segment":[394],"selection":[395],"technique":[396,461],"normalization":[399],"relies":[403],"discriminative":[406,470,496],"reliable":[408,433],"utterance":[413],"verify":[415],"speaker.":[417],"particularly":[421],"useful":[422],"noisy":[424],"where":[426],"using":[427],"activity":[429],"detection":[430],"at":[434],"level.":[437],"source":[439],"comes":[443],"fact":[446],"all":[449],"phonemes":[450],"equally":[452],"discriminative.":[453],"To":[454],"address":[455],"this,":[456],"re-weighting":[460],"applied":[463],"likelihood":[465],"values":[466],"level":[471],"each":[473,477],"Gaussian":[474,492],"component,":[475],"i.e.":[476],"particular":[478],"region":[479],"space.":[483],"It":[484],"found":[486],"limited":[489],"number":[490],"mixtures,":[493],"herein":[494],"components":[497,511],"responsible":[499],"overall":[502],"performance,":[503],"inclusion":[506],"other":[509],"non-discriminative":[510],"may":[512],"degrade":[514],"performance.":[517]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
