{"id":"https://openalex.org/W4405181820","doi":"https://doi.org/10.1145/3658644.3690305","title":"Blind and Low-Vision Individuals' Detection of Audio Deepfakes","display_name":"Blind and Low-Vision Individuals' Detection of Audio Deepfakes","publication_year":2024,"publication_date":"2024-12-02","ids":{"openalex":"https://openalex.org/W4405181820","doi":"https://doi.org/10.1145/3658644.3690305"},"language":"en","primary_location":{"id":"doi:10.1145/3658644.3690305","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3658644.3690305","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3658644.3690305","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3658644.3690305","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089811277","display_name":"Filipo Sharevski","orcid":"https://orcid.org/0000-0003-3058-7255"},"institutions":[{"id":"https://openalex.org/I118353179","display_name":"DePaul University","ror":"https://ror.org/04xtx5t16","country_code":"US","type":"education","lineage":["https://openalex.org/I118353179"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Filipo Sharevski","raw_affiliation_strings":["DePaul University, Chicago, Illinois, USA"],"affiliations":[{"raw_affiliation_string":"DePaul University, Chicago, Illinois, USA","institution_ids":["https://openalex.org/I118353179"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092669381","display_name":"Aziz Zeidieh","orcid":"https://orcid.org/0009-0000-9334-8660"},"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":"Aziz Zeidieh","raw_affiliation_strings":["University of Illinois Urbana-Champaign, Urbana-Champaign, Illinois, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign, Urbana-Champaign, Illinois, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057939229","display_name":"Jennifer Vander Loop","orcid":"https://orcid.org/0009-0000-1333-9968"},"institutions":[{"id":"https://openalex.org/I118353179","display_name":"DePaul University","ror":"https://ror.org/04xtx5t16","country_code":"US","type":"education","lineage":["https://openalex.org/I118353179"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jennifer Vander Loop","raw_affiliation_strings":["DePaul University, Chicago, Illinois, USA"],"affiliations":[{"raw_affiliation_string":"DePaul University, Chicago, Illinois, USA","institution_ids":["https://openalex.org/I118353179"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075383234","display_name":"Peter Jachim","orcid":"https://orcid.org/0000-0001-9238-6710"},"institutions":[{"id":"https://openalex.org/I118353179","display_name":"DePaul University","ror":"https://ror.org/04xtx5t16","country_code":"US","type":"education","lineage":["https://openalex.org/I118353179"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peter Jachim","raw_affiliation_strings":["DePaul University, Chicago, Illinois, USA"],"affiliations":[{"raw_affiliation_string":"DePaul University, Chicago, Illinois, USA","institution_ids":["https://openalex.org/I118353179"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5089811277"],"corresponding_institution_ids":["https://openalex.org/I118353179"],"apc_list":null,"apc_paid":null,"fwci":1.3158,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.82597593,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4867","last_page":"4881"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9983000159263611,"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"}},"topics":[{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9983000159263611,"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"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9957000017166138,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.993399977684021,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discernment","display_name":"Discernment","score":0.8445857763290405},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5326696634292603},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.48139098286628723},{"id":"https://openalex.org/keywords/fluency","display_name":"Fluency","score":0.47584056854248047},{"id":"https://openalex.org/keywords/articulation","display_name":"Articulation (sociology)","score":0.45677700638771057},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.42156392335891724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4133721590042114},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.370873361825943},{"id":"https://openalex.org/keywords/politics","display_name":"Politics","score":0.1346726417541504},{"id":"https://openalex.org/keywords/mathematics-education","display_name":"Mathematics education","score":0.09327811002731323}],"concepts":[{"id":"https://openalex.org/C2780211513","wikidata":"https://www.wikidata.org/wiki/Q1132167","display_name":"Discernment","level":2,"score":0.8445857763290405},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5326696634292603},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.48139098286628723},{"id":"https://openalex.org/C2777413886","wikidata":"https://www.wikidata.org/wiki/Q3276013","display_name":"Fluency","level":2,"score":0.47584056854248047},{"id":"https://openalex.org/C2779337067","wikidata":"https://www.wikidata.org/wiki/Q4800961","display_name":"Articulation (sociology)","level":3,"score":0.45677700638771057},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.42156392335891724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4133721590042114},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.370873361825943},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.1346726417541504},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.09327811002731323},{"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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:10.1145/3658644.3690305","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3658644.3690305","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3658644.3690305","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3658644.3690305","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3658644.3690305","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3658644.3690305","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405181820.pdf","grobid_xml":"https://content.openalex.org/works/W4405181820.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W2010266308","https://openalex.org/W2049686551","https://openalex.org/W2060895888","https://openalex.org/W2143597468","https://openalex.org/W2760645782","https://openalex.org/W2796189892","https://openalex.org/W3127827332","https://openalex.org/W3128666957","https://openalex.org/W3131786367","https://openalex.org/W3157576687","https://openalex.org/W3159367349","https://openalex.org/W3166900385","https://openalex.org/W3186285959","https://openalex.org/W4381198892","https://openalex.org/W4385080277","https://openalex.org/W4386033764","https://openalex.org/W4392903621","https://openalex.org/W4396833689","https://openalex.org/W4402264376","https://openalex.org/W4405181820"],"related_works":["https://openalex.org/W2022692657","https://openalex.org/W4385350114","https://openalex.org/W3082280736","https://openalex.org/W3137448783","https://openalex.org/W2604207088","https://openalex.org/W2787896723","https://openalex.org/W1970852015","https://openalex.org/W1586553505","https://openalex.org/W4289981698","https://openalex.org/W3013539567"],"abstract_inverted_index":{"Audio":[0,25],"deepfakes":[1,26,141,239],"are":[2,11,44],"a":[3,22,56,80,85,110,191],"form":[4],"of":[5,21,68,82,94,130,144,159,162,173,176,193,228],"deception":[6],"where":[7],"convincing":[8],"speech":[9,53,204],"sentences":[10],"synthesized":[12],"through":[13],"machine":[14],"learning":[15],"means":[16],"to":[17,77,165,243],"give":[18],"an":[19,29,59,65,126],"impression":[20],"human":[23],"speaker.":[24],"emerge":[27],"as":[28,41,55,71,105,135,152,170,206,231],"attractive":[30],"vector":[31],"for":[32],"targeting":[33],"users":[34],"that":[35,150,168,182,237],"rely":[36,73],"on":[37,52,75,101],"audio":[38,83,238],"accessibility,":[39],"such":[40,104],"individuals":[42,119,247],"who":[43],"blind":[45,115],"or":[46,87],"low":[47,117],"vision.":[48],"The":[49,148,209],"critical":[50],"reliance":[51,100],"both":[54],"medium":[57],"and":[58,116,132,199,223,226,256,259,266],"affordance":[60],"puts":[61],"this":[62,95],"population":[63],"at":[64],"undue":[66],"risk":[67,96],"being":[69],"deceived":[70],"they":[72],"solely":[74],"themselves":[76],"detect":[78],"whether":[79],"piece":[81],"is":[84],"deepfake":[86],"not.":[88],"To":[89],"better":[90,157],"understand":[91],"the":[92,98,121,145,166,183,186,197,200,203,212,218,224,229,241],"nature":[93],"considering":[97],"nuanced":[99],"assistive":[102],"technologies":[103],"screen":[106],"readers,":[107],"we":[108],"conducted":[109],"user":[111],"study":[112],"with":[113,248,263],"n=16":[114],"vision":[118],"from":[120],"US.":[122],"Our":[123,178],"participants":[124,149,184,210,235],"achieved":[125],"overall":[127],"discernment":[128,207,232],"accuracy":[129],"59%,":[131],"clips":[133],"identified":[134],"deep":[136],"fakes":[137],"were":[138],"only":[139],"actually":[140],"in":[142,185,196,202,211,254],"50.8%":[143],"cases":[146],"(precision).":[147],"self-identified":[151,169],"\"low":[153,213],"vision\"":[154,214],"performed":[155],"slightly":[156],"(accuracy":[158,172],"61%,":[160],"precision":[161,175],"64%)":[163],"compared":[164],"ones":[167],"\"blind\"":[171,187],"55%,":[174],"56%).":[177],"qualitative":[179],"results":[180],"show":[181],"group":[188,215],"mostly":[189,216],"considered":[190],"combination":[192],"infliction,":[194],"imperfections":[195],"voice,":[198],"intensity":[201],"delivery":[205],"factors.":[208],"used":[217],"speaker's":[219],"pitch,":[220],"enunciation,":[221],"emotion,":[222],"fluency":[225],"articulation":[227],"speaker":[230],"cues.":[233],"Overall,":[234],"felt":[236],"have":[240],"potential":[242],"deceive":[244],"visually":[245],"impaired":[246],"political":[249],"disinformation,":[250],"impersonate":[251],"their":[252],"voice":[253,264],"authentication":[255],"smart":[257],"homes,":[258],"specifically":[260],"target":[261],"them":[262],"phishing":[265],"enhanced":[267],"scams.":[268]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
