{"id":"https://openalex.org/W7225384757","doi":"https://doi.org/10.17743/jaes.2026.0308","title":"Sound of the Mix: Identifying Mixing Engineers With Deep Learning","display_name":"Sound of the Mix: Identifying Mixing Engineers With Deep Learning","publication_year":2026,"publication_date":"2026-11-06","ids":{"openalex":"https://openalex.org/W7225384757","doi":"https://doi.org/10.17743/jaes.2026.0308"},"language":"en","primary_location":{"id":"doi:10.17743/jaes.2026.0308","doi":"https://doi.org/10.17743/jaes.2026.0308","is_oa":false,"landing_page_url":"https://doi.org/10.17743/jaes.2026.0308","pdf_url":null,"source":{"id":"https://openalex.org/S62507282","display_name":"Journal of the Audio Engineering Society","issn_l":"1549-4950","issn":["1549-4950"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","erih-plus","jufo-2","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4320800558","host_organization_name":"Audio Engineering Society","host_organization_lineage":["https://openalex.org/P4320800558"],"host_organization_lineage_names":["Audio Engineering Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Audio Engineering Society","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5031259320","display_name":"Matteo Marciano","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Matteo Marciano","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019170864","display_name":"Himadri Mukherjee","orcid":"https://orcid.org/0000-0002-6570-1356","observed_orcids":["https://orcid.org/0000-0002-6570-1356"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Himadri Mukherjee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050072264","display_name":"Ankita Dhar","orcid":"https://orcid.org/0000-0003-1122-2250","observed_orcids":["https://orcid.org/0000-0003-1122-2250"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ankita Dhar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5015792060","display_name":"Kaushik Roy","orcid":"https://orcid.org/0000-0002-3360-7576","observed_orcids":["https://orcid.org/0000-0002-3360-7576"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaushik Roy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"74","issue":"11","first_page":"868","last_page":"876"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":1.0,"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":1.0,"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/T11349","display_name":"Music Technology and Sound Studies","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1210","display_name":"Music"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.0,"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/music-mixing","display_name":"music mixing","score":0.6380000114440918},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8069999814033508},{"id":"https://openalex.org/keywords/audio-classification","display_name":"audio classification","score":0.4950000047683716}],"concepts":[{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.7531999945640564},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.7429999709129333},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6859999895095825},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6158999800682068},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5881999731063843},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5698000192642212},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4047999978065491},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3465999960899353},{"id":"https://openalex.org/C2780544925","wikidata":"https://www.wikidata.org/wiki/Q569874","display_name":"Surround sound","level":3,"score":0.34220001101493835},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.3418000042438507},{"id":"https://openalex.org/C203718221","wikidata":"https://www.wikidata.org/wiki/Q491713","display_name":"Sound (geography)","level":2,"score":0.34049999713897705},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3118000030517578},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30730000138282776},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2808000147342682},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.27390000224113464},{"id":"https://openalex.org/C127220857","wikidata":"https://www.wikidata.org/wiki/Q2719318","display_name":"Audio signal processing","level":4,"score":0.2718999981880188},{"id":"https://openalex.org/C2778348673","wikidata":"https://www.wikidata.org/wiki/Q739302","display_name":"Production (economics)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.25619998574256897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.17743/jaes.2026.0308","doi":"https://doi.org/10.17743/jaes.2026.0308","is_oa":false,"landing_page_url":"https://doi.org/10.17743/jaes.2026.0308","pdf_url":null,"source":{"id":"https://openalex.org/S62507282","display_name":"Journal of the Audio Engineering Society","issn_l":"1549-4950","issn":["1549-4950"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","erih-plus","jufo-2","norway-1","poland-70","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4320800558","host_organization_name":"Audio Engineering Society","host_organization_lineage":["https://openalex.org/P4320800558"],"host_organization_lineage_names":["Audio Engineering Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Audio Engineering Society","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4293169095","https://openalex.org/W2216282080","https://openalex.org/W4313560685","https://openalex.org/W3093608541","https://openalex.org/W2330052555","https://openalex.org/W4398770094","https://openalex.org/W4416190242","https://openalex.org/W4411141958","https://openalex.org/W2791449361","https://openalex.org/W6996974722"],"abstract_inverted_index":{"Advances":[0],"in":[1,17,56,102],"music":[2,21,29],"production":[3],"technology":[4],"at":[5],"both":[6],"hardware":[7],"and":[8,39,82,112,127,156],"software":[9],"levels":[10],"have":[11],"led":[12],"to":[13,117,138],"a":[14,58,69,88,146,160],"substantial":[15],"increase":[16],"the":[18,25,153,182,185],"volume":[19],"of":[20,27,76,148,164,184],"released":[22],"annually,":[23],"motivating":[24],"development":[26],"automated":[28,43],"categorization":[30,44],"systems":[31],"based":[32,45],"on":[33,46,145],"attributes":[34],"such":[35],"as":[36],"artist,":[37],"genre,":[38],"mood.":[40],"In":[41],"contrast,":[42],"mixing":[47,94,172],"engineers":[48,64,95],"remains":[49],"largely":[50],"unexplored,":[51],"despite":[52],"their":[53],"critical":[54],"role":[55],"shaping":[57],"song\u2019s":[59],"final":[60],"sonic":[61,99,141],"identity.":[62],"Mixing":[63],"translate":[65],"artistic":[66],"intent":[67],"into":[68],"cohesive":[70],"auditory":[71],"experience":[72],"through":[73],"nuanced":[74],"control":[75],"frequency":[77],"balance,":[78],"dynamics,":[79],"spatial":[80],"depth,":[81],"stereo":[83,103,109],"imaging.":[84],"This":[85],"paper":[86],"proposes":[87],"deep":[89],"learning\u2013based":[90],"framework":[91],"for":[92,178],"identifying":[93],"by":[96,170],"analyzing":[97],"distinctive":[98],"characteristics":[100],"embedded":[101],"audio":[104],"recordings.":[105],"The":[106,122,166],"approach":[107],"processes":[108],"channels":[110],"individually":[111],"isolates":[113],"key":[114],"interchannel":[115],"components":[116],"capture":[118],"subtle":[119],"mixing-related":[120],"cues.":[121],"extracted":[123],"representations":[124],"are":[125,136],"visualized":[126],"processed":[128],"using":[129],"dedicated":[130],"convolutional":[131],"neural":[132],"networks,":[133],"whose":[134],"outputs":[135],"fused":[137],"enable":[139],"multidimensional":[140],"analysis.":[142],"Experimental":[143],"evaluation":[144],"dataset":[147],"60":[149],"songs,":[150],"predominantly":[151],"spanning":[152],"modern":[154],"rock":[155],"metal":[157],"spectrum,":[158],"achieved":[159],"maximum":[161],"classification":[162],"accuracy":[163],"92.86%.":[165],"recordings":[167],"were":[168],"produced":[169],"six":[171],"engineers,":[173],"with":[174],"artist-related":[175],"similarities":[176],"controlled":[177],"during":[179],"evaluation,":[180],"demonstrating":[181],"effectiveness":[183],"proposed":[186],"method.":[187]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-11-07T00:00:00"}