{"id":"https://openalex.org/W3083146453","doi":"https://doi.org/10.1109/access.2020.3021711","title":"Knowledge Distillation in Acoustic Scene Classification","display_name":"Knowledge Distillation in Acoustic Scene Classification","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3083146453","doi":"https://doi.org/10.1109/access.2020.3021711","mag":"3083146453"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3021711","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3021711","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09186616.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09186616.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091834525","display_name":"Jee-weon Jung","orcid":"https://orcid.org/0000-0003-0505-2988"},"institutions":[{"id":"https://openalex.org/I124633538","display_name":"University of Seoul","ror":"https://ror.org/05en5nh73","country_code":"KR","type":"education","lineage":["https://openalex.org/I124633538"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jee-Weon Jung","raw_affiliation_strings":["School of Computer Science, University of Seoul, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Seoul, Seoul, South Korea","institution_ids":["https://openalex.org/I124633538"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070613375","display_name":"Hee-Soo Heo","orcid":"https://orcid.org/0000-0003-1567-123X"},"institutions":[{"id":"https://openalex.org/I60922564","display_name":"Naver (South Korea)","ror":"https://ror.org/04nzrnx83","country_code":"KR","type":"company","lineage":["https://openalex.org/I60922564"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hee-Soo Heo","raw_affiliation_strings":["Naver Corporation, Seongnam, South Korea"],"affiliations":[{"raw_affiliation_string":"Naver Corporation, Seongnam, South Korea","institution_ids":["https://openalex.org/I60922564"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103211980","display_name":"Hye-jin Shim","orcid":null},"institutions":[{"id":"https://openalex.org/I124633538","display_name":"University of Seoul","ror":"https://ror.org/05en5nh73","country_code":"KR","type":"education","lineage":["https://openalex.org/I124633538"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hye-Jin Shim","raw_affiliation_strings":["School of Computer Science, University of Seoul, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Seoul, Seoul, South Korea","institution_ids":["https://openalex.org/I124633538"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030475312","display_name":"Ha-Jin Yu","orcid":"https://orcid.org/0000-0003-3657-0665"},"institutions":[{"id":"https://openalex.org/I124633538","display_name":"University of Seoul","ror":"https://ror.org/05en5nh73","country_code":"KR","type":"education","lineage":["https://openalex.org/I124633538"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ha-Jin Yu","raw_affiliation_strings":["School of Computer Science, University of Seoul, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Seoul, Seoul, South Korea","institution_ids":["https://openalex.org/I124633538"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091834525"],"corresponding_institution_ids":["https://openalex.org/I124633538"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.1136,"has_fulltext":true,"cited_by_count":32,"citation_normalized_percentile":{"value":0.94889412,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"166870","last_page":"166879"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9997000098228455,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9955000281333923,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.814355731010437},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7420784831047058},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6707314848899841},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5229880809783936},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5176106691360474},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.499021053314209},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4984879493713379},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.48580384254455566},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4459267854690552},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4149113595485687},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14569500088691711}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.814355731010437},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7420784831047058},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6707314848899841},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5229880809783936},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5176106691360474},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.499021053314209},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4984879493713379},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.48580384254455566},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4459267854690552},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4149113595485687},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14569500088691711},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3021711","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3021711","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09186616.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:65973a18b4164f86a84ddf2022cd9446","is_oa":true,"landing_page_url":"https://doaj.org/article/65973a18b4164f86a84ddf2022cd9446","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 166870-166879 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3021711","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3021711","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09186616.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6899999976158142,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G216598507","display_name":null,"funder_award_id":"2020R1A2C1007081","funder_id":"https://openalex.org/F4320322030","funder_display_name":"Ministry of Science, ICT and Future Planning"},{"id":"https://openalex.org/G342704958","display_name":null,"funder_award_id":"funded","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G7997151884","display_name":null,"funder_award_id":"2020R1A2C1007081","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322030","display_name":"Ministry of Science, ICT and Future Planning","ror":"https://ror.org/032e49973"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3083146453.pdf","grobid_xml":"https://content.openalex.org/works/W3083146453.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1836465849","https://openalex.org/W2133564696","https://openalex.org/W2194775991","https://openalex.org/W2302255633","https://openalex.org/W2327501763","https://openalex.org/W2402040300","https://openalex.org/W2520774990","https://openalex.org/W2626967530","https://openalex.org/W2765407302","https://openalex.org/W2785523195","https://openalex.org/W2889151164","https://openalex.org/W2913795158","https://openalex.org/W2921763313","https://openalex.org/W2952524552","https://openalex.org/W2957789971","https://openalex.org/W2963096935","https://openalex.org/W2972369255","https://openalex.org/W2972548957","https://openalex.org/W2973149080","https://openalex.org/W2980792518","https://openalex.org/W2982415754","https://openalex.org/W2982461124","https://openalex.org/W2982500554","https://openalex.org/W2982683041","https://openalex.org/W2987897905","https://openalex.org/W3008104819","https://openalex.org/W3015530480","https://openalex.org/W3017925328","https://openalex.org/W3027169863","https://openalex.org/W3029899047","https://openalex.org/W3040691452","https://openalex.org/W4289465850","https://openalex.org/W4295312788","https://openalex.org/W4295723153","https://openalex.org/W4385245566","https://openalex.org/W6638523607","https://openalex.org/W6638667902","https://openalex.org/W6679434410","https://openalex.org/W6712847557","https://openalex.org/W6739651123","https://openalex.org/W6739901393","https://openalex.org/W6745136726","https://openalex.org/W6747620207","https://openalex.org/W6752516136","https://openalex.org/W6756022612","https://openalex.org/W6758876586","https://openalex.org/W6760395818","https://openalex.org/W6765212446","https://openalex.org/W6766978945","https://openalex.org/W6778029303","https://openalex.org/W6778248386","https://openalex.org/W6780512329"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W3026162553","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W3000197790","https://openalex.org/W4315865067","https://openalex.org/W3208304128","https://openalex.org/W2979433843"],"abstract_inverted_index":{"Common":[0],"acoustic":[1,11,26,76,109,176,193],"properties":[2],"that":[3,47,73,101,111,147,185,218],"different":[4,71],"classes":[5,72],"share":[6,74],"degrades":[7],"the":[8,68,162,171,186,200,207,215,222,248],"performance":[9,149],"of":[10,25,32,108,132,136,157,175,202,240,247],"scene":[12,194],"classification":[13,174,238],"systems.":[14],"This":[15],"results":[16],"in":[17,92,192,206],"a":[18,21,29,43,97,105,142,237],"phenomenon":[19],"where":[20],"few":[22],"confusing":[23],"pairs":[24,131],"scenes":[27,110,177],"dominate":[28],"significant":[30],"proportion":[31],"all":[33],"misclassified":[34,203],"audio":[35,204],"segments.":[36],"In":[37],"this":[38,93,137],"article,":[39],"we":[40],"propose":[41,80],"adopting":[42],"knowledge":[44,163,187,224],"distillation":[45,188,225],"framework":[46,189],"trains":[48],"deep":[49,61,98,123,144],"neural":[50,62,99,124,145],"networks":[51,125],"using":[52,170,232],"soft":[53,87],"labels.":[54,88],"Soft":[55],"labels,":[56],"extracted":[57],"from":[58,164,226],"another":[59],"pre-trained":[60],"network,":[63],"are":[64,112],"used":[65],"to":[66,84,96,126,140],"reflect":[67],"similarity":[69],"between":[70],"similar":[75],"properties.":[77],"We":[78],"also":[79],"utilizing":[81],"specialist":[82,90,122],"models":[83,197],"provide":[85],"additional":[86],"Each":[89],"model":[91,213],"study":[94],"refers":[95],"network":[100,146],"concentrates":[102],"on":[103,129],"discriminating":[104],"single":[106,143,212],"pair":[107],"frequently":[113],"misclassified.":[114],"Self":[115],"multi-head":[116],"attention":[117,234],"is":[118,139,190,219],"explored":[119],"for":[120],"training":[121],"further":[127],"concentrate":[128],"target":[130,208],"classes.":[133,209],"The":[134,210],"goal":[135],"article":[138],"train":[141],"demonstrates":[148],"equivalent":[150],"to,":[151],"or":[152],"higher":[153,243],"than,":[154],"an":[155,233,245],"ensemble":[156,246],"multiple":[158,251],"models,":[159,228],"by":[160,221],"distilling":[161],"several":[165,227],"models.":[166],"Diverse":[167],"experiments":[168],"conducted":[169],"detection":[172],"and":[173,178,250],"events":[179],"2019":[180],"task":[181],"1-a":[182],"dataset":[183],"demonstrate":[184],"effective":[191],"classification.":[195],"Specialist":[196],"successfully":[198],"decrease":[199],"number":[201],"segments":[205],"final":[211],"with":[214],"proposed":[216,223],"method":[217],"trained":[220,231],"including":[229],"specialists":[230],"mechanism,":[235],"shows":[236],"accuracy":[239],"77.63":[241],"%,":[242],"than":[244],"baseline":[249],"specialists.":[252]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}