{"id":"https://openalex.org/W4415974762","doi":"https://doi.org/10.1016/j.procs.2025.09.288","title":"Discerning Music Genres: Exploring Neural Network Architectures for Automated Classification","display_name":"Discerning Music Genres: Exploring Neural Network Architectures for Automated Classification","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415974762","doi":"https://doi.org/10.1016/j.procs.2025.09.288"},"language":"en","primary_location":{"id":"doi:10.1016/j.procs.2025.09.288","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2025.09.288","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1016/j.procs.2025.09.288","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017117771","display_name":"Eric Odle","orcid":"https://orcid.org/0000-0002-3141-042X"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Eric Odle","raw_affiliation_strings":["Graduate School of Science, Hokkaido University, 5 Chome Kita 8 Jonishi, Kita Ward, Sapporo, Hokkaido 060-0808, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Science, Hokkaido University, 5 Chome Kita 8 Jonishi, Kita Ward, Sapporo, Hokkaido 060-0808, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062487478","display_name":"Pei\u2010Chun Lin","orcid":"https://orcid.org/0000-0001-9146-3817"},"institutions":[{"id":"https://openalex.org/I4880106","display_name":"Feng Chia University","ror":"https://ror.org/05vhczg54","country_code":"TW","type":"education","lineage":["https://openalex.org/I4880106"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Pei-Chun Lin","raw_affiliation_strings":["Department of Information Engineering and Computer Science, Feng Chia University, No. 100, Wenhwa Road, Seatwen, Taichung 40724, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, Feng Chia University, No. 100, Wenhwa Road, Seatwen, Taichung 40724, Taiwan","institution_ids":["https://openalex.org/I4880106"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091894566","display_name":"Amin Farjudian","orcid":"https://orcid.org/0000-0002-1879-0763"},"institutions":[{"id":"https://openalex.org/I79619799","display_name":"University of Birmingham","ror":"https://ror.org/03angcq70","country_code":"GB","type":"education","lineage":["https://openalex.org/I79619799"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Amin Farjudian","raw_affiliation_strings":["School of Mathematics, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom","institution_ids":["https://openalex.org/I79619799"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062487478"],"corresponding_institution_ids":["https://openalex.org/I4880106"],"apc_list":null,"apc_paid":null,"fwci":1.2668,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"270","issue":null,"first_page":"1679","last_page":"1688"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9139999747276306,"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":0.9139999747276306,"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/T10788","display_name":"Neuroscience and Music Perception","score":0.009800000116229057,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11349","display_name":"Music Technology and Sound Studies","score":0.00430000014603138,"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/hyperparameter","display_name":"Hyperparameter","score":0.7251999974250793},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6416000127792358},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6238999962806702},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5758000016212463},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5393999814987183},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.48260000348091125},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4453999996185303}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9133999943733215},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.7251999974250793},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6416000127792358},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6248999834060669},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6238999962806702},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5758000016212463},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5412999987602234},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5393999814987183},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4453999996185303},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.3560999929904938},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.32919999957084656},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.31380000710487366},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C2777946086","wikidata":"https://www.wikidata.org/wiki/Q1163335","display_name":"Music information retrieval","level":3,"score":0.26010000705718994}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.procs.2025.09.288","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2025.09.288","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire/0307e6f3-1bb1-4132-b400-95bac449ed7f","is_oa":true,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/0307e6f3-1bb1-4132-b400-95bac449ed7f","pdf_url":"https://pure-oai.bham.ac.uk/ws/files/282522855/2025-Odle_Lin_Farjudian-Discerning_Music_Genres-Exploring_Neural_Network_Architectures_for_Automated_Classification.pdf","source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Odle, E, Lin, P C & Farjudian, A 2025, 'Discerning music genres : Exploring neural network architectures for automated classification', Procedia Computer Science, vol. 270, pp. 1679-1688. https://doi.org/10.1016/j.procs.2025.09.288","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.1016/j.procs.2025.09.288","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.procs.2025.09.288","pdf_url":null,"source":{"id":"https://openalex.org/S120348307","display_name":"Procedia Computer Science","issn_l":"1877-0509","issn":["1877-0509"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Procedia Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8392764252","display_name":null,"funder_award_id":"NSTC 113-2221-E-035-072","funder_id":"https://openalex.org/F4320323842","funder_display_name":"Feng Chia University"}],"funders":[{"id":"https://openalex.org/F2461203286","display_name":"National Science and Technology Council","ror":"https://ror.org/02kv4zf79"},{"id":"https://openalex.org/F4320323842","display_name":"Feng Chia University","ror":"https://ror.org/05vhczg54"},{"id":"https://openalex.org/F4320331164","display_name":"National Science and Technology Council","ror":"https://ror.org/00wnb9798"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1934057878","https://openalex.org/W1987404672","https://openalex.org/W2040870580","https://openalex.org/W2053225842","https://openalex.org/W2062826588","https://openalex.org/W2083517661","https://openalex.org/W2088312083","https://openalex.org/W2098950511","https://openalex.org/W2100483895","https://openalex.org/W2100700860","https://openalex.org/W2101315546","https://openalex.org/W2108598243","https://openalex.org/W2128033389","https://openalex.org/W2128196382","https://openalex.org/W2133824856","https://openalex.org/W2156798505","https://openalex.org/W2157331557","https://openalex.org/W2159561775","https://openalex.org/W2191779130","https://openalex.org/W2368080971","https://openalex.org/W2554247923","https://openalex.org/W2593116425","https://openalex.org/W2603766943","https://openalex.org/W2612138235","https://openalex.org/W2799194071","https://openalex.org/W2889391573","https://openalex.org/W2951413354","https://openalex.org/W2963100531","https://openalex.org/W3006951794","https://openalex.org/W3017229010","https://openalex.org/W3017637887","https://openalex.org/W3036286896","https://openalex.org/W3049459827","https://openalex.org/W3095319910","https://openalex.org/W3124497955","https://openalex.org/W3143373604","https://openalex.org/W3174689080","https://openalex.org/W3210797221","https://openalex.org/W4221161255","https://openalex.org/W4223422326","https://openalex.org/W4225849234","https://openalex.org/W4250107139","https://openalex.org/W4292622404","https://openalex.org/W4293150093","https://openalex.org/W4297013360","https://openalex.org/W4300402905","https://openalex.org/W4312632513","https://openalex.org/W4368367148","https://openalex.org/W4387120668","https://openalex.org/W4390187154","https://openalex.org/W4391846670","https://openalex.org/W4392529729"],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1],"investigates":[2],"the":[3,18,26,86,107],"application":[4],"of":[5,20,88,109],"various":[6],"artificial":[7],"neural":[8,36,40],"network":[9],"(ANN)":[10],"architectures":[11],"for":[12],"music":[13,118,139],"genre":[14,53,119,140],"classification,":[15],"focusing":[16],"on":[17,25,125],"evolution":[19],"models":[21],"and":[22,43,50,63,73,97,114,135],"their":[23,48],"performance":[24,134],"GTZAN":[27],"dataset.":[28],"Through":[29],"experimentation":[30],"with":[31],"fully":[32],"connected":[33],"networks,":[34],"convolutional":[35],"networks":[37,41],"(CNNs),":[38],"recurrent":[39,75],"(RNNs),":[42],"Transformer-based":[44],"architectures,":[45],"we":[46],"analyze":[47],"strengths":[49],"limitations":[51],"in":[52,83,101,117,138],"classification.":[54,120],"The":[55],"results":[56,105],"demonstrate":[57],"that":[58],"hyperparameter":[59],"tuning,":[60],"dataset":[61,115],"diversity,":[62],"model":[64,112,136],"selection":[65],"significantly":[66],"impact":[67],"classification":[68,95,133,141],"performance.":[69],"Although":[70],"CNNs,":[71],"RNNs,":[72],"gated":[74],"units":[76],"(GRUs)":[77],"achieve":[78],"more":[79],"precision":[80],"than":[81],"90%":[82],"evaluation":[84],"tests,":[85],"addition":[87],"Transformer":[89],"layers":[90],"does":[91],"not":[92],"consistently":[93],"improve":[94],"accuracy":[96],"may":[98],"exacerbate":[99],"challenges":[100],"certain":[102],"genres.":[103],"These":[104],"underscore":[106],"importance":[108],"carefully":[110],"considering":[111],"architecture":[113],"characteristics":[116],"Future":[121],"research":[122],"should":[123],"focus":[124],"developing":[126],"extensive,":[127],"multi-rater":[128],"verified":[129],"datasets":[130],"to":[131],"enhance":[132],"robustness":[137],"tasks.":[142]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-22T07:34:49.880490","created_date":"2025-11-06T00:00:00"}
