{"id":"https://openalex.org/W4416251166","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229182","title":"CombinedNet: A Hybrid Model for Deepfake Audio Detection Using Deep Learning Techniques","display_name":"CombinedNet: A Hybrid Model for Deepfake Audio Detection Using Deep Learning Techniques","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251166","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229182"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11229182","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229182","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5019105782","display_name":"Vincenzo Gattulli","orcid":"https://orcid.org/0000-0001-9974-9414"},"institutions":[{"id":"https://openalex.org/I5561750","display_name":"University of Bari Aldo Moro","ror":"https://ror.org/027ynra39","country_code":"IT","type":"education","lineage":["https://openalex.org/I5561750"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Vincenzo Gattulli","raw_affiliation_strings":["University of Bari \"Aldo Moro\",Department of Computer Science,Bari"],"affiliations":[{"raw_affiliation_string":"University of Bari \"Aldo Moro\",Department of Computer Science,Bari","institution_ids":["https://openalex.org/I5561750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000811181","display_name":"Donato Impedovo","orcid":"https://orcid.org/0000-0002-9285-2555"},"institutions":[{"id":"https://openalex.org/I5561750","display_name":"University of Bari Aldo Moro","ror":"https://ror.org/027ynra39","country_code":"IT","type":"education","lineage":["https://openalex.org/I5561750"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Donato Impedovo","raw_affiliation_strings":["University of Bari \"Aldo Moro\",Department of Computer Science,Bari"],"affiliations":[{"raw_affiliation_string":"University of Bari \"Aldo Moro\",Department of Computer Science,Bari","institution_ids":["https://openalex.org/I5561750"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5019105782"],"corresponding_institution_ids":["https://openalex.org/I5561750"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37413445,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.4341000020503998,"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":0.4341000020503998,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.3727000057697296,"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/T11309","display_name":"Music and Audio Processing","score":0.019700000062584877,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.828000009059906},{"id":"https://openalex.org/keywords/benchmarking","display_name":"Benchmarking","score":0.7555000185966492},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.670799970626831},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6037999987602234},{"id":"https://openalex.org/keywords/digital-audio","display_name":"Digital audio","score":0.42829999327659607}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.828000009059906},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7721999883651733},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.7555000185966492},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6990000009536743},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.670799970626831},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6037999987602234},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5182999968528748},{"id":"https://openalex.org/C87687168","wikidata":"https://www.wikidata.org/wiki/Q173114","display_name":"Digital audio","level":4,"score":0.42829999327659607},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.41990000009536743},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.31529998779296875},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2985000014305115}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11229182","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229182","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2904540497","https://openalex.org/W2997510749","https://openalex.org/W3008818273","https://openalex.org/W3135057216","https://openalex.org/W4328028667","https://openalex.org/W4385781832","https://openalex.org/W4385800847","https://openalex.org/W4388893647","https://openalex.org/W4392529044","https://openalex.org/W4394019163"],"related_works":[],"abstract_inverted_index":{"In":[0,40],"the":[1,55,85,89],"digital":[2],"age,":[3],"deepfakes":[4],"pose":[5],"a":[6,15,43],"growing":[7],"threat":[8],"to":[9],"information":[10],"security":[11],"and":[12,24,36,76],"integrity,":[13],"with":[14],"particular":[16],"focus":[17],"on":[18,63,69],"audio":[19,30,95],"fakes.":[20],"This":[21],"paper":[22],"explores":[23],"compares":[25],"different":[26],"machine-learning":[27],"techniques":[28],"for":[29],"deepfake":[31,96],"detection,":[32],"analyzing":[33],"both":[34],"deep":[35,50],"shallow":[37],"learning-based":[38],"approaches.":[39],"particular,":[41],"CombinedNet,":[42],"novel":[44],"model":[45],"obtained":[46],"by":[47],"combining":[48],"two":[49],"learning":[51],"networks":[52],"selected":[53],"from":[54],"literature,":[56],"is":[57],"presented.":[58],"Performance":[59],"evaluation":[60],"was":[61],"conducted":[62],"public":[64],"datasets":[65],"through":[66],"benchmarking":[67],"based":[68],"standard":[70],"metrics":[71],"such":[72],"as":[73],"accuracy,":[74],"precision,":[75],"F1-score.":[77],"The":[78],"experimental":[79],"results":[80],"show":[81],"that":[82],"CombinedNet":[83],"outperforms":[84],"benchmark":[86],"models,":[87],"highlighting":[88],"potential":[90],"of":[91],"hybrid":[92],"solutions":[93],"in":[94],"detection.":[97]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}
