{"id":"https://openalex.org/W4414321962","doi":"https://doi.org/10.1109/access.2025.3611839","title":"Deepfake Audio Detection: A Comparative Study of Advanced Deep Learning Models","display_name":"Deepfake Audio Detection: A Comparative Study of Advanced Deep Learning Models","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414321962","doi":"https://doi.org/10.1109/access.2025.3611839"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3611839","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3611839","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3611839","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004461235","display_name":"Kavya Verma","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kavya Verma","raw_affiliation_strings":["School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0009-0007-0029-2743","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119665338","display_name":"Divyanshi Mittal","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Divyanshi Mittal","raw_affiliation_strings":["School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0009-0001-3235-7042","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Sagnik Samanta","orcid":"https://orcid.org/0009-0008-0217-1758"},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sagnik Samanta","raw_affiliation_strings":["School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0009-0008-0217-1758","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119665339","display_name":"Kabir Gulati","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kabir Gulati","raw_affiliation_strings":["School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0009-0001-3715-2310","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112226434","display_name":"Ojas Kulkarni","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ojas Kulkarni","raw_affiliation_strings":["School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0009-0000-7944-0911","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099843011","display_name":"Muzaffar Ahmad Dar","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Muzaffar Ahmad Dar","raw_affiliation_strings":["School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0009-0009-0037-9341","affiliations":[{"raw_affiliation_string":"School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029154020","display_name":"C. L. Biji","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"C. L. Biji","raw_affiliation_strings":["School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0000-0001-6655-4450","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India","institution_ids":["https://openalex.org/I876193797"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I876193797"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.8885,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.87298786,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"13","issue":null,"first_page":"168447","last_page":"168462"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9485999941825867,"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"}},"topics":[{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9485999941825867,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.927299976348877,"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/deep-learning","display_name":"Deep learning","score":0.7159000039100647},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6287000179290771},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5964000225067139},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5691999793052673},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.49219998717308044},{"id":"https://openalex.org/keywords/replicate","display_name":"Replicate","score":0.4794999957084656},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4300999939441681},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39250001311302185},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3474999964237213}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8935999870300293},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7159000039100647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6638000011444092},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6287000179290771},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5964000225067139},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5691999793052673},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.49219998717308044},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.4794999957084656},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4300999939441681},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.40380001068115234},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39250001311302185},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3481000065803528},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3474999964237213},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.3450999855995178},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3330000042915344},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.32109999656677246},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C64922751","wikidata":"https://www.wikidata.org/wiki/Q4650799","display_name":"Audio signal","level":3,"score":0.3118000030517578},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.3082999885082245},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.26910001039505005}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3611839","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3611839","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0591eca816904d5d895e838d2c1c0db5","is_oa":true,"landing_page_url":"https://doaj.org/article/0591eca816904d5d895e838d2c1c0db5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 168447-168462 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3611839","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3611839","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2148154194","https://openalex.org/W2745896134","https://openalex.org/W2889361425","https://openalex.org/W2903442965","https://openalex.org/W3026777299","https://openalex.org/W3200527256","https://openalex.org/W3213515747","https://openalex.org/W4206030489","https://openalex.org/W4220758433","https://openalex.org/W4256161595","https://openalex.org/W4285362588","https://openalex.org/W4380990703","https://openalex.org/W4388851105","https://openalex.org/W4388893647","https://openalex.org/W4399412254","https://openalex.org/W4399556751","https://openalex.org/W4400051874","https://openalex.org/W4401991736","https://openalex.org/W4402037602","https://openalex.org/W4402600203","https://openalex.org/W4403054584","https://openalex.org/W4403217519","https://openalex.org/W4403766366","https://openalex.org/W4404075079","https://openalex.org/W4404083962","https://openalex.org/W4404143292","https://openalex.org/W4404345434","https://openalex.org/W4405709115","https://openalex.org/W4408609339","https://openalex.org/W4409295775"],"related_works":[],"abstract_inverted_index":{"The":[0,141,195],"rapid":[1],"advancements":[2],"in":[3,187],"artificial":[4],"intelligence":[5],"(AI)":[6],"have":[7],"significantly":[8],"enhanced":[9],"audio":[10,71,77],"synthesis":[11,44],"capabilities,":[12],"enabling":[13],"deepfake":[14,76,218],"technology":[15],"to":[16,28,55,73],"replicate":[17],"human":[18],"speech":[19,43],"with":[20,109,148,174,189,202],"near-perfect":[21],"accuracy.":[22],"This":[23],"poses":[24],"severe":[25],"security":[26],"threats":[27],"various":[29],"domains,":[30],"including":[31],"banking,":[32],"customer":[33],"service,":[34],"and":[35,52,65,113,132,161,185,192,204,212],"law":[36],"enforcement,":[37],"as":[38,47],"malicious":[39],"actors":[40],"can":[41],"exploit":[42],"techniques":[45],"such":[46],"voice":[48],"conversion,":[49],"replay":[50],"attacks,":[51],"text-to-speech":[53],"(TTS)":[54],"manipulate":[56],"or":[57],"impersonate":[58],"individuals.":[59],"In":[60],"this":[61],"study,":[62],"both":[63],"spectral":[64,191,203],"temporal":[66,193,205],"features":[67],"were":[68,139],"extracted":[69],"from":[70],"recordings":[72],"explore":[74],"state-of-the-art":[75],"detection":[78],"frameworks,":[79],"highlighting":[80],"the":[81,89,92,124,152,168,214],"effectiveness":[82],"of":[83,91,122,177],"advanced":[84],"deep":[85],"learning":[86],"methods.":[87],"Specifically,":[88],"performance":[90,216],"bidirectional":[93,114],"long":[94],"short-term":[95],"memory":[96],"(BLSTM)":[97],"network,":[98],"a":[99,105,133,208],"custom":[100],"convolutional":[101],"neural":[102],"network":[103,126],"(CNN),":[104],"residual":[106,125],"CNN":[107,136],"integrated":[108],"an":[110],"attention":[111],"mechanism":[112],"gated":[115],"recurrent":[116],"unit":[117],"(ResCNN-Attention-BGRU),":[118],"WIREnet":[119,162],"(a":[120],"variant":[121],"BLSTM),":[123],"for":[127,217],"fully":[128],"connected":[129],"(ResNet":[130],"FC),":[131],"squeeze-and-excitation-enhanced":[134],"one-dimensional":[135],"(SE-Enhanced":[137],"1D-CNN)":[138],"compared.":[140],"proposed":[142],"models":[143],"achieved":[144,213],"notable":[145],"testing":[146],"accuracies,":[147],"SE-Enhanced":[149],"1D-CNN":[150],"reaching":[151],"highest":[153],"at":[154],"97.64%,":[155],"followed":[156],"by":[157],"ResNet":[158],"FC":[159],"(97.46%)":[160],"(97.20%),":[163],"demonstrating":[164],"strong":[165],"generalization":[166],"across":[167],"evaluated":[169],"architectures.":[170],"Furthermore,":[171],"we":[172],"experimented":[173],"different":[175],"numbers":[176],"mel-frequency":[178],"cepstral":[179],"coefficients":[180],"(MFCCs),":[181],"specifically":[182],"13,":[183],"26,":[184],"39,":[186],"combination":[188],"other":[190],"features.":[194],"experimental":[196],"results":[197],"demonstrated":[198],"that":[199],"MFCC-39,":[200],"together":[201],"features,":[206],"had":[207],"robust":[209],"feature":[210],"representation":[211],"best":[215],"detection.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-01T08:55:40.977307","created_date":"2025-10-10T00:00:00"}