{"id":"https://openalex.org/W2736090641","doi":"https://doi.org/10.1109/ijcnn.2017.7966273","title":"Acoustic novelty detection with adversarial autoencoders","display_name":"Acoustic novelty detection with adversarial autoencoders","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2736090641","doi":"https://doi.org/10.1109/ijcnn.2017.7966273","mag":"2736090641"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2017.7966273","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966273","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5004777557","display_name":"Emanuele Principi","orcid":"https://orcid.org/0000-0002-2835-7277"},"institutions":[{"id":"https://openalex.org/I122534668","display_name":"Marche Polytechnic University","ror":"https://ror.org/00x69rs40","country_code":"IT","type":"education","lineage":["https://openalex.org/I122534668"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Emanuele Principi","raw_affiliation_strings":["Department of Information Engineering, Universit\u00e0 Politecnica delle Marche, Ancona, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Universit\u00e0 Politecnica delle Marche, Ancona, Italy","institution_ids":["https://openalex.org/I122534668"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009982837","display_name":"Fabio Vesperini","orcid":"https://orcid.org/0000-0001-7748-5454"},"institutions":[{"id":"https://openalex.org/I122534668","display_name":"Marche Polytechnic University","ror":"https://ror.org/00x69rs40","country_code":"IT","type":"education","lineage":["https://openalex.org/I122534668"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Fabio Vesperini","raw_affiliation_strings":["Department of Information Engineering, Universit\u00e0 Politecnica delle Marche, Ancona, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Universit\u00e0 Politecnica delle Marche, Ancona, Italy","institution_ids":["https://openalex.org/I122534668"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034253968","display_name":"Stefano Squartini","orcid":"https://orcid.org/0000-0001-9374-0128"},"institutions":[{"id":"https://openalex.org/I122534668","display_name":"Marche Polytechnic University","ror":"https://ror.org/00x69rs40","country_code":"IT","type":"education","lineage":["https://openalex.org/I122534668"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Stefano Squartini","raw_affiliation_strings":["Department of Information Engineering, Universit\u00e0 Politecnica delle Marche, Ancona, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Universit\u00e0 Politecnica delle Marche, Ancona, Italy","institution_ids":["https://openalex.org/I122534668"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004758092","display_name":"Francesco Piazza","orcid":"https://orcid.org/0000-0003-0205-3790"},"institutions":[{"id":"https://openalex.org/I122534668","display_name":"Marche Polytechnic University","ror":"https://ror.org/00x69rs40","country_code":"IT","type":"education","lineage":["https://openalex.org/I122534668"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Piazza","raw_affiliation_strings":["Department of Information Engineering, Universit\u00e0 Politecnica delle Marche, Ancona, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Universit\u00e0 Politecnica delle Marche, Ancona, Italy","institution_ids":["https://openalex.org/I122534668"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5004777557"],"corresponding_institution_ids":["https://openalex.org/I122534668"],"apc_list":null,"apc_paid":null,"fwci":4.0955,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.95158794,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3324","last_page":"3330"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9988999962806702,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9988999962806702,"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/T11309","display_name":"Music and Audio Processing","score":0.9959999918937683,"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/T11220","display_name":"Water Systems and Optimization","score":0.9560999870300293,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8793326616287231},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.8735206127166748},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7070569396018982},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6310782432556152},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6304187774658203},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5216691493988037},{"id":"https://openalex.org/keywords/novelty-detection","display_name":"Novelty detection","score":0.5193513631820679},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5057485103607178},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.47068551182746887},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.44411152601242065},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.41495510935783386},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.30524271726608276},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.09515690803527832}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8793326616287231},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.8735206127166748},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7070569396018982},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6310782432556152},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6304187774658203},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5216691493988037},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.5193513631820679},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5057485103607178},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.47068551182746887},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.44411152601242065},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.41495510935783386},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.30524271726608276},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.09515690803527832},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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":2,"locations":[{"id":"doi:10.1109/ijcnn.2017.7966273","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2017.7966273","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.univpm.it:11566/252454","is_oa":false,"landing_page_url":"http://ieeexplore.ieee.org/document/7966273/","pdf_url":null,"source":{"id":"https://openalex.org/S4306402571","display_name":"Universit\u00e0 Politecnica delle Marche (Universit\u00e0 Politecnica delle Marche)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I122534668","host_organization_name":"Marche Polytechnic University","host_organization_lineage":["https://openalex.org/I122534668"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1486001387","https://openalex.org/W1499399937","https://openalex.org/W1522301498","https://openalex.org/W1601124178","https://openalex.org/W1636210188","https://openalex.org/W1654762370","https://openalex.org/W1836465849","https://openalex.org/W1844944916","https://openalex.org/W1965833531","https://openalex.org/W1970578576","https://openalex.org/W1990190154","https://openalex.org/W2014706377","https://openalex.org/W2018383168","https://openalex.org/W2043641277","https://openalex.org/W2050969847","https://openalex.org/W2064675550","https://openalex.org/W2066662427","https://openalex.org/W2070707809","https://openalex.org/W2076068958","https://openalex.org/W2076885544","https://openalex.org/W2090777335","https://openalex.org/W2095345875","https://openalex.org/W2097998348","https://openalex.org/W2099471712","https://openalex.org/W2102113734","https://openalex.org/W2103434133","https://openalex.org/W2105497548","https://openalex.org/W2108287924","https://openalex.org/W2111702192","https://openalex.org/W2115627867","https://openalex.org/W2148154194","https://openalex.org/W2157665255","https://openalex.org/W2337344967","https://openalex.org/W2405774341","https://openalex.org/W2410396934","https://openalex.org/W2474046725","https://openalex.org/W2574572704","https://openalex.org/W2751660967","https://openalex.org/W4239510810","https://openalex.org/W4293568373","https://openalex.org/W4297814361","https://openalex.org/W4320013936","https://openalex.org/W6629077442","https://openalex.org/W6647839309","https://openalex.org/W6674385629","https://openalex.org/W6675365184","https://openalex.org/W6683235873","https://openalex.org/W6713658392","https://openalex.org/W6714145577","https://openalex.org/W6720514713","https://openalex.org/W6929467385"],"related_works":["https://openalex.org/W2064636555","https://openalex.org/W2585503716","https://openalex.org/W1939982668","https://openalex.org/W2105014086","https://openalex.org/W2076090200","https://openalex.org/W4312933423","https://openalex.org/W3025682415","https://openalex.org/W2995944953","https://openalex.org/W1532481220","https://openalex.org/W2081173909"],"abstract_inverted_index":{"Novelty":[0],"detection":[1],"is":[2,35,63,78,140,160],"the":[3,8,48,81,85,88,91,101,106,110,116,123,145,148,154,165,171,174,180,190,198,211,217],"task":[4,242],"of":[5,13,37,59,90,100,109,114,147,173,179,216],"recognising":[6],"events":[7],"differ":[9],"from":[10,47,153,189],"a":[11,38,57,68,94,137,186,202,223,249],"model":[12],"normality.":[14],"This":[15],"paper":[16],"proposes":[17],"an":[18,28,52,71,133],"acoustic":[19,61],"novelty":[20,77],"detector":[21],"based":[22],"on":[23,56,185,240],"neural":[24],"networks":[25],"trained":[26,55,141,161],"with":[27,222,229],"adversarial":[29,134],"training":[30,107,118,155,251],"strategy.":[31],"The":[32,97,157,177,194,214,233],"proposed":[33,102,199],"approach":[34,103,200,235],"composed":[36],"feature":[39],"extraction":[40],"stage":[41],"that":[42,120,197],"calculates":[43],"Log-Mel":[44],"spectral":[45],"features":[46],"input":[49,86],"signal.":[50],"Then,":[51],"autoencoder":[53,92,111,149],"network,":[54],"corpus":[58,187],"\u201cnormal\u201d":[60],"signals,":[62],"employed":[64],"to":[65,142,207,210],"detect":[66],"whether":[67],"segment":[69],"contains":[70],"abnormal":[72],"event":[73],"or":[74],"not.":[75],"A":[76],"detected":[79],"if":[80,255],"Euclidean":[82],"distance":[83],"between":[84,144],"and":[87,150,226,243],"output":[89,146,172],"exceeds":[93],"certain":[95],"threshold.":[96],"innovative":[98],"contribution":[99],"resides":[104],"in":[105],"procedure":[108,119],"network:":[112],"instead":[113],"using":[115,164],"conventional":[117],"minimises":[121],"only":[122],"Minimum":[124],"Mean":[125],"Squared":[126],"Error":[127],"loss":[128,168],"function,":[129],"here":[130],"we":[131],"adopt":[132],"strategy,":[135],"where":[136],"discriminator":[138,175],"network":[139],"distinguish":[143],"data":[151],"sampled":[152],"corpus.":[156],"autoencoder,":[158],"then,":[159],"also":[162],"by":[163,257],"binary":[166],"cross-entropy":[167],"calculated":[169],"at":[170],"network.":[176],"performance":[178,204],"algorithm":[181],"has":[182,219],"been":[183,220],"assessed":[184],"derived":[188],"PASCAL":[191],"CHiME":[192],"dataset.":[193],"results":[195,239],"showed":[196,237],"provides":[201],"relative":[203],"improvement":[205,218],"equal":[206],"0.26%":[208],"compared":[209],"standard":[212],"autoencoder.":[213],"significance":[215],"evaluated":[221],"one-tailed":[224],"z-test":[225],"resulted":[227],"significant":[228],"p":[230],"<;":[231],"0.001.":[232],"presented":[234],"thus":[236],"promising":[238],"this":[241],"it":[244],"could":[245],"be":[246],"extended":[247],"as":[248],"general":[250],"strategy":[252],"for":[253],"autoencoders":[254],"confirmed":[256],"additional":[258],"experiments.":[259]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":5}],"updated_date":"2025-12-01T00:03:43.161839","created_date":"2025-10-10T00:00:00"}