{"id":"https://openalex.org/W4200305276","doi":"https://doi.org/10.1109/waspaa52581.2021.9632679","title":"Adaptive Generalized Cross-Entropy Loss for Sound Event Classification with Noisy Labels","display_name":"Adaptive Generalized Cross-Entropy Loss for Sound Event Classification with Noisy Labels","publication_year":2021,"publication_date":"2021-10-17","ids":{"openalex":"https://openalex.org/W4200305276","doi":"https://doi.org/10.1109/waspaa52581.2021.9632679"},"language":"en","primary_location":{"id":"doi:10.1109/waspaa52581.2021.9632679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/waspaa52581.2021.9632679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://mediatum.ub.tum.de/1648099","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104020575","display_name":"Jun Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jun Deng","raw_affiliation_strings":["Deep Learning Department,Munich,AG,Germany,81477"],"affiliations":[{"raw_affiliation_string":"Deep Learning Department,Munich,AG,Germany,81477","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007792998","display_name":"Chunhui Gao","orcid":"https://orcid.org/0009-0008-3135-1133"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chunhui Gao","raw_affiliation_strings":["Deep Learning Department,Munich,AG,Germany,81477"],"affiliations":[{"raw_affiliation_string":"Deep Learning Department,Munich,AG,Germany,81477","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102224294","display_name":"Qian Feng","orcid":"https://orcid.org/0000-0002-7048-1239"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian Feng","raw_affiliation_strings":["Deep Learning Department,Munich,AG,Germany,81477"],"affiliations":[{"raw_affiliation_string":"Deep Learning Department,Munich,AG,Germany,81477","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049684805","display_name":"Xinzhou Xu","orcid":"https://orcid.org/0000-0002-4017-5919"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinzhou Xu","raw_affiliation_strings":["School of Internet of Things, Nanjing University of Posts and Telecommunications, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Internet of Things, Nanjing University of Posts and Telecommunications, P. R. China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101705037","display_name":"Zhaopeng Chen","orcid":"https://orcid.org/0000-0003-0375-9146"},"institutions":[{"id":"https://openalex.org/I159176309","display_name":"Universit\u00e4t Hamburg","ror":"https://ror.org/00g30e956","country_code":"DE","type":"education","lineage":["https://openalex.org/I159176309"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Zhaopeng Chen","raw_affiliation_strings":["Munich, AG, Germany","TAMS (Technical Aspects of Multimodal Systems), University of Hamburg"],"affiliations":[{"raw_affiliation_string":"Munich, AG, Germany","institution_ids":[]},{"raw_affiliation_string":"TAMS (Technical Aspects of Multimodal Systems), University of Hamburg","institution_ids":["https://openalex.org/I159176309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5104020575"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4571,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63191346,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"256","last_page":"260"},"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":0.9836999773979187,"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":0.9824000000953674,"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/computer-science","display_name":"Computer science","score":0.7590416073799133},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5906489491462708},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.5709154605865479},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.5372974276542664},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5263071060180664},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.4999361038208008},{"id":"https://openalex.org/keywords/data-loss","display_name":"Data loss","score":0.49358904361724854},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.46405306458473206},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4468023180961609},{"id":"https://openalex.org/keywords/information-loss","display_name":"Information loss","score":0.4291078746318817},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4236214756965637},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41616323590278625},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.35413068532943726},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.32241347432136536},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3060842752456665},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.13614684343338013}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7590416073799133},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5906489491462708},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.5709154605865479},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.5372974276542664},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5263071060180664},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.4999361038208008},{"id":"https://openalex.org/C193519340","wikidata":"https://www.wikidata.org/wiki/Q891179","display_name":"Data loss","level":2,"score":0.49358904361724854},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.46405306458473206},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4468023180961609},{"id":"https://openalex.org/C2988416141","wikidata":"https://www.wikidata.org/wiki/Q6031139","display_name":"Information loss","level":2,"score":0.4291078746318817},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4236214756965637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41616323590278625},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35413068532943726},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.32241347432136536},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3060842752456665},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.13614684343338013},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/waspaa52581.2021.9632679","is_oa":false,"landing_page_url":"https://doi.org/10.1109/waspaa52581.2021.9632679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)","raw_type":"proceedings-article"},{"id":"pmh:oai:mediatum.ub.tum.de:node/1648099","is_oa":true,"landing_page_url":"https://mediatum.ub.tum.de/1648099","pdf_url":null,"source":{"id":"https://openalex.org/S4377196330","display_name":"mediaTUM  (Technical University of Munich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I62916508","host_organization_name":"Technical University of Munich","host_organization_lineage":["https://openalex.org/I62916508"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"ConferencePaper"}],"best_oa_location":{"id":"pmh:oai:mediatum.ub.tum.de:node/1648099","is_oa":true,"landing_page_url":"https://mediatum.ub.tum.de/1648099","pdf_url":null,"source":{"id":"https://openalex.org/S4377196330","display_name":"mediaTUM  (Technical University of Munich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I62916508","host_organization_name":"Technical University of Munich","host_organization_lineage":["https://openalex.org/I62916508"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"ConferencePaper"},"sustainable_development_goals":[{"score":0.5299999713897705,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G5250479028","display_name":null,"funder_award_id":"61801241","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8613823656","display_name":null,"funder_award_id":"DFG TRR-169/NSFC 61621136008","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W205159212","https://openalex.org/W2050752817","https://openalex.org/W2071712938","https://openalex.org/W2106241685","https://openalex.org/W2121056381","https://openalex.org/W2135131618","https://openalex.org/W2165163503","https://openalex.org/W2167460663","https://openalex.org/W2169138660","https://openalex.org/W2296193698","https://openalex.org/W2509065397","https://openalex.org/W2589599921","https://openalex.org/W2593116425","https://openalex.org/W2618574054","https://openalex.org/W2620673134","https://openalex.org/W2761514455","https://openalex.org/W2770119437","https://openalex.org/W2803187616","https://openalex.org/W2884535146","https://openalex.org/W2900681352","https://openalex.org/W2923802272","https://openalex.org/W2941678425","https://openalex.org/W2947463580","https://openalex.org/W2953102540","https://openalex.org/W2963697299","https://openalex.org/W2963859210","https://openalex.org/W2972386832","https://openalex.org/W2990019157","https://openalex.org/W3098357269","https://openalex.org/W4254607142","https://openalex.org/W6608394925","https://openalex.org/W6678280073","https://openalex.org/W6684426735","https://openalex.org/W6736098614","https://openalex.org/W6737985840","https://openalex.org/W6738763127","https://openalex.org/W6746278845","https://openalex.org/W6749488094","https://openalex.org/W6751420435","https://openalex.org/W6753583920","https://openalex.org/W6758854760"],"related_works":["https://openalex.org/W1026011007","https://openalex.org/W1888231326","https://openalex.org/W2951959408","https://openalex.org/W2895831313","https://openalex.org/W2163643788","https://openalex.org/W2212380038","https://openalex.org/W2082971787","https://openalex.org/W4289406078","https://openalex.org/W2346921268","https://openalex.org/W4313270457"],"abstract_inverted_index":{"Considering":[0],"the":[1,15,23,40,59,69,118,122,132,146],"high":[2],"cost":[3],"of":[4,48,66,121],"manually":[5],"annotated":[6],"large-scale":[7],"datasets":[8],"for":[9],"superior":[10],"sound":[11],"event":[12],"classifier":[13],"performance,":[14],"data":[16,143],"collection":[17],"process":[18],"has":[19],"shifted":[20],"to":[21,58,98,104],"using":[22],"Internet,":[24],"which":[25,67,74,95],"facilitates":[26],"easier":[27],"user-contributed":[28],"audio":[29],"and":[30,85,109,115,127,134],"metadata":[31],"collection.":[32],"However,":[33,78],"label":[34,44],"noise":[35,83,107],"is":[36,68,149],"inevitable.":[37],"To":[38],"address":[39],"problems":[41],"caused":[42],"by":[43,152],"noise,":[45],"several":[46],"types":[47],"noise-robust":[49],"loss":[50,124,148],"functions":[51],"have":[52],"been":[53],"proposed":[54,123,147],"recently":[55],"as":[56],"alternatives":[57],"commonly":[60],"categorical":[61],"cross-entropy":[62,71],"(CCE)":[63],"loss,":[64,73,94],"one":[65],"generalized":[70],"(GCE)":[72],"demonstrates":[75],"state-of-the-art":[76],"performance.":[77],"GCE":[79,93,135],"cannot":[80],"realize":[81],"sufficient":[82,110],"robustness":[84,108],"satisfactory":[86],"accuracy":[87,120],"simultaneously.":[88],"Thus,":[89],"we":[90],"propose":[91],"adaptive":[92],"automatically":[96],"adapts":[97],"noisy":[99],"labels":[100],"in":[101,145],"every":[102],"batch":[103],"achieve":[105],"adequate":[106],"accuracy.":[111],"We":[112,138],"conducted":[113],"experiments":[114],"found":[116],"that":[117,141],"classification":[119],"demonstrated":[125],"4.7%":[126],"1.2%":[128],"absolute":[129],"improvement":[130],"over":[131],"CCE":[133],"baselines,":[136],"respectively.":[137],"also":[139],"demonstrate":[140],"clean":[142],"consumption":[144],"dramatically":[150],"reduced":[151],"more":[153],"than":[154],"75%":[155],"compared":[156],"with":[157],"CCE.":[158]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}