{"id":"https://openalex.org/W7133528127","doi":"https://doi.org/10.48550/arxiv.2603.02781","title":"Scores Know Bobs Voice: Speaker Impersonation Attack","display_name":"Scores Know Bobs Voice: Speaker Impersonation Attack","publication_year":2026,"publication_date":"2026-03-03","ids":{"openalex":"https://openalex.org/W7133528127","doi":"https://doi.org/10.48550/arxiv.2603.02781"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.02781","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02781","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.02781","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027004914","display_name":"Chul-Hee Hwang","orcid":"https://orcid.org/0009-0008-0789-1316"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hwang, Chanwoo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009893717","display_name":"Sunpill Kim","orcid":"https://orcid.org/0000-0002-7767-4084"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Sunpill","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021598141","display_name":"Yong Kiam Tan","orcid":"https://orcid.org/0000-0001-7033-2463"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Yong Kiam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128078464","display_name":"Tianchi Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Tianchi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089876418","display_name":"Seunghun Paik","orcid":"https://orcid.org/0000-0003-1105-1607"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Paik, Seunghun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103518400","display_name":"Dongsoo Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kim, Dongsoo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038733121","display_name":"Mondal Soumik","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Soumik, Mondal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058648309","display_name":"Khin Mi Mi Aung","orcid":"https://orcid.org/0000-0002-5652-3455"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aung, Khin Mi Mi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5045700517","display_name":"Jae Hong Seo","orcid":"https://orcid.org/0000-0003-0547-5702"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seo, Jae Hong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5027004914"],"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":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.6391000151634216,"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":0.6391000151634216,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.210099995136261,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.02199999988079071,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7541999816894531},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6407999992370605},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5102999806404114},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4821999967098236},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4819999933242798},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4722999930381775},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.46880000829696655},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4219000041484833}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.78329998254776},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7541999816894531},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6407999992370605},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5102999806404114},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4821999967098236},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4819999933242798},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4722999930381775},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.46880000829696655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.421999990940094},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4219000041484833},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.4196999967098236},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.40869998931884766},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.39309999346733093},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3847000002861023},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38100001215934753},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.36899998784065247},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.36160001158714294},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3472999930381775},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.3440999984741211},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.31189998984336853},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3027999997138977},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.25920000672340393},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.25440001487731934},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.02781","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02781","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.02781","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.02781","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7573409080505371,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Advances":[0],"in":[1,42],"deep":[2],"learning":[3],"have":[4],"enabled":[5,202],"the":[6,38,81,103,107,111,120,169,201,225],"widespread":[7],"deployment":[8],"of":[9,34,40,106,115,122,171,227],"speaker":[10,141],"recognition":[11],"systems":[12],"(SRSs),":[13],"yet":[14],"they":[15],"remain":[16],"vulnerable":[17],"to":[18,37,78,85,168,207],"score-based":[19,127,231],"impersonation":[20,232],"attacks.":[21],"Existing":[22],"attacks":[23,128],"that":[24,100,135,146,178],"operate":[25],"directly":[26,149],"on":[27,191],"raw":[28],"waveforms":[29],"require":[30],"a":[31,72,131,172,220],"large":[32],"number":[33],"queries":[35,195],"due":[36,167],"difficulty":[39],"optimizing":[41],"high-dimensional":[43],"audio":[44],"spaces.":[45],"Latent-space":[46],"optimization":[47,74],"within":[48],"generative":[49,97],"models":[50],"offers":[51],"improved":[52],"efficiency,":[53,184],"but":[54],"these":[55],"latent":[56,104,138,147],"spaces":[57],"are":[58],"shaped":[59],"by":[60],"data":[61],"distribution":[62],"matching":[63],"and":[64,129],"do":[65],"not":[66],"inherently":[67],"capture":[68],"speaker-discriminative":[69],"geometry.":[70],"As":[71],"result,":[73],"trajectories":[75],"often":[76],"fail":[77],"align":[79],"with":[80,110,140,190],"adversarial":[82],"direction":[83],"needed":[84],"maximize":[86],"victim":[87],"scores.":[88],"To":[89],"address":[90],"this":[91],"limitation,":[92],"we":[93],"propose":[94],"an":[95,123],"inversion-based":[96],"attack":[98,158,187,204],"framework":[99],"explicitly":[101],"aligns":[102],"space":[105,114],"synthesis":[108],"model":[109,125],"discriminative":[112],"feature":[113],"SRSs.":[116],"We":[117],"first":[118],"analyze":[119],"requirements":[121],"inverse":[124],"for":[126,223],"introduce":[130],"feature-aligned":[132,217],"inversion":[133,218],"strategy":[134],"geometrically":[136],"synchronizes":[137],"representations":[139],"embeddings.":[142],"This":[143],"alignment":[144],"ensures":[145],"updates":[148],"translate":[150],"into":[151],"score":[152],"improvements.":[153],"Moreover,":[154],"it":[155],"enables":[156],"new":[157],"paradigms,":[159],"including":[160],"subspace-projection-based":[161,203],"attacks,":[162],"which":[163],"were":[164],"previously":[165],"infeasible":[166],"absence":[170],"faithful":[173],"feature-to-audio":[174],"mapping.":[175],"Experiments":[176],"show":[177],"our":[179],"method":[180],"significantly":[181],"improves":[182],"query":[183],"achieving":[185],"competitive":[186],"success":[188,209],"rates":[189],"average":[192],"10x":[193],"fewer":[194],"than":[196],"prior":[197],"approaches.":[198],"In":[199],"particular,":[200],"attains":[205],"up":[206],"91.65%":[208],"using":[210],"only":[211],"50":[212],"queries.":[213],"These":[214],"findings":[215],"establish":[216],"as":[219],"key":[221],"tool":[222],"evaluating":[224],"robustness":[226],"modern":[228],"SRSs":[229],"against":[230],"threats.":[233]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-03-05T00:00:00"}