{"id":"https://openalex.org/W7153261476","doi":"https://doi.org/10.48550/arxiv.2604.08450","title":"DeepFense: A Unified, Modular, and Extensible Framework for Robust Deepfake Audio Detection","display_name":"DeepFense: A Unified, Modular, and Extensible Framework for Robust Deepfake Audio Detection","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7153261476","doi":"https://doi.org/10.48550/arxiv.2604.08450"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.08450","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08450","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.2604.08450","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133322577","display_name":"Yassine El Kheir","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kheir, Yassine El","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133323255","display_name":"Arnab Das","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Das, Arnab","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066827611","display_name":"Yixuan Xiao","orcid":"https://orcid.org/0009-0005-0461-9374"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Yixuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133382924","display_name":"Xin Wang","orcid":"https://orcid.org/0000-0003-0536-9010"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124911191","display_name":"Feidi Kallel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kallel, Feidi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Erdogan, Enes Erdem","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Erdogan, Enes Erdem","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133351049","display_name":"Ngoc Thang Vu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vu, Ngoc Thang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034570279","display_name":"Tim Polzehl","orcid":"https://orcid.org/0000-0001-9592-0296"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Polzehl, Tim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5102948543","display_name":"Sebastian Moeller","orcid":"https://orcid.org/0000-0002-0381-6449"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Moeller, Sebastian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5133322577"],"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":0.5120999813079834,"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":0.5120999813079834,"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":0.2296999990940094,"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":0.03359999880194664,"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/software-deployment","display_name":"Software deployment","score":0.6158999800682068},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5888000130653381},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.5593000054359436},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5166000127792358},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4846999943256378},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4607999920845032},{"id":"https://openalex.org/keywords/extensibility","display_name":"Extensibility","score":0.4147999882698059},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.3846000134944916}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.832099974155426},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.6158999800682068},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5888000130653381},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.5593000054359436},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5166000127792358},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4846999943256378},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4812000095844269},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4607999920845032},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4496000111103058},{"id":"https://openalex.org/C32833848","wikidata":"https://www.wikidata.org/wiki/Q4115054","display_name":"Extensibility","level":2,"score":0.4147999882698059},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.3846000134944916},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3547999858856201},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3334999978542328},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3095000088214874},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.3005000054836273},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.27070000767707825},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.08450","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08450","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.2604.08450","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.08450","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":[{"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5","score":0.7173862457275391}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Speech":[0],"deepfake":[1],"detection":[2],"is":[3,106],"a":[4,37,59],"well-established":[5],"research":[6],"field":[7],"with":[8,112],"different":[9],"models,":[10],"datasets,":[11],"and":[12,21,27,48,103,122],"training":[13,74,119],"strategies.":[14],"However,":[15],"the":[16,43,79,113],"lack":[17],"of":[18,62,81],"standardized":[19],"implementations":[20],"evaluation":[22,61],"protocols":[23],"limits":[24],"reproducibility,":[25],"benchmarking,":[26],"comparison":[28],"across":[29],"studies.":[30],"In":[31],"this":[32],"work,":[33],"we":[34,57,91],"present":[35],"DeepFense,":[36,56],"comprehensive,":[38],"open-source":[39],"PyTorch":[40],"toolkit":[41],"integrating":[42],"latest":[44],"architectures,":[45],"loss":[46],"functions,":[47],"augmentation":[49],"pipelines,":[50],"alongside":[51],"over":[52],"100":[53],"recipes.":[54],"Using":[55],"conducted":[58],"large-scale":[60],"more":[63],"than":[64],"400":[65],"models.":[66],"Our":[67],"findings":[68],"reveal":[69],"that":[70],"while":[71],"carefully":[72],"curated":[73],"data":[75,120],"improves":[76],"cross-domain":[77],"generalization,":[78],"choice":[80],"pre-trained":[82],"front-end":[83,123],"feature":[84],"extractor":[85],"dominates":[86],"overall":[87],"performance":[88],"variance.":[89],"Crucially,":[90],"show":[92],"severe":[93],"biases":[94],"in":[95],"high-performing":[96],"models":[97],"regarding":[98],"audio":[99],"quality,":[100],"speaker":[101],"gender,":[102],"language.":[104],"DeepFense":[105],"expected":[107],"to":[108,116],"facilitate":[109],"real-world":[110],"deployment":[111],"necessary":[114],"tools":[115],"address":[117],"equitable":[118],"selection":[121],"fine-tuning.":[124]},"counts_by_year":[],"updated_date":"2026-05-03T08:25:01.440150","created_date":"2026-04-11T00:00:00"}