{"id":"https://openalex.org/W3015384913","doi":"https://doi.org/10.1109/icassp40776.2020.9053582","title":"Acoustic Scene Classification for Mismatched Recording Devices Using Heated-Up Softmax and Spectrum Correction","display_name":"Acoustic Scene Classification for Mismatched Recording Devices Using Heated-Up Softmax and Spectrum Correction","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015384913","doi":"https://doi.org/10.1109/icassp40776.2020.9053582","mag":"3015384913"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053582","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5100764742","display_name":"Truc Nguyen","orcid":"https://orcid.org/0000-0002-5234-4601"},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Truc Nguyen","raw_affiliation_strings":["SPSC Institute, Graz University of Technology, Austria"],"affiliations":[{"raw_affiliation_string":"SPSC Institute, Graz University of Technology, Austria","institution_ids":["https://openalex.org/I4092182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015798259","display_name":"Franz Pernkopf","orcid":"https://orcid.org/0000-0002-6356-3367"},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Franz Pernkopf","raw_affiliation_strings":["SPSC Institute, Graz University of Technology, Austria"],"affiliations":[{"raw_affiliation_string":"SPSC Institute, Graz University of Technology, Austria","institution_ids":["https://openalex.org/I4092182"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007416983","display_name":"Micha\u0142 Ko\u015bmider","orcid":null},"institutions":[{"id":"https://openalex.org/I4092182","display_name":"Graz University of Technology","ror":"https://ror.org/00d7xrm67","country_code":"AT","type":"education","lineage":["https://openalex.org/I4092182"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Michal Kosmider","raw_affiliation_strings":["SPSC Institute, Graz University of Technology, Austria"],"affiliations":[{"raw_affiliation_string":"SPSC Institute, Graz University of Technology, Austria","institution_ids":["https://openalex.org/I4092182"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100764742"],"corresponding_institution_ids":["https://openalex.org/I4092182"],"apc_list":null,"apc_paid":null,"fwci":3.7884,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.94075049,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"126","last_page":"130"},"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":0.9998999834060669,"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":0.9994000196456909,"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/softmax-function","display_name":"Softmax function","score":0.9730676412582397},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7513028383255005},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6807011961936951},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5745040774345398},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5429461002349854},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.540190577507019},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.504226565361023},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.46520501375198364},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.4319726228713989},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42785608768463135},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08756580948829651}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9730676412582397},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7513028383255005},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6807011961936951},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5745040774345398},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5429461002349854},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.540190577507019},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.504226565361023},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.46520501375198364},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.4319726228713989},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42785608768463135},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08756580948829651},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053582","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053582","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W2626967530","https://openalex.org/W2765407302","https://openalex.org/W2883935097","https://openalex.org/W2885782501","https://openalex.org/W2890619523","https://openalex.org/W2902200315","https://openalex.org/W2902772991","https://openalex.org/W2921763313","https://openalex.org/W2936774411","https://openalex.org/W2963351448","https://openalex.org/W2964212410","https://openalex.org/W2966337730","https://openalex.org/W3015530480","https://openalex.org/W4294648858","https://openalex.org/W4295723153","https://openalex.org/W6638523607","https://openalex.org/W6745136726","https://openalex.org/W6756508168","https://openalex.org/W6760395818"],"related_works":["https://openalex.org/W2769441402","https://openalex.org/W2594436708","https://openalex.org/W4360994128","https://openalex.org/W3086240734","https://openalex.org/W2951850672","https://openalex.org/W2789476480","https://openalex.org/W4300326282","https://openalex.org/W2742395793","https://openalex.org/W2810018382","https://openalex.org/W3042419602"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"(DNNs)":[3],"are":[4],"successful":[5],"in":[6,40,58],"applications":[7],"with":[8,21,46,93,150,170],"matching":[9],"inference":[10],"and":[11,60,124,127,163,181],"training":[12],"distributions.":[13],"In":[14,71,83],"realworld":[15],"scenarios,":[16],"DNNs":[17],"have":[18],"to":[19,79,91,102,114],"cope":[20],"truly":[22],"new":[23],"data":[24,33,63,107],"samples":[25],"during":[26],"inference,":[27],"potentially":[28],"coming":[29],"from":[30],"a":[31,38,109],"shifted":[32,106],"distribution.":[34],"This":[35],"usually":[36],"causes":[37,68],"drop":[39],"performance.":[41],"Acoustic":[42],"scene":[43],"classification":[44,158],"(ASC)":[45],"different":[47,66],"recording":[48,99],"devices":[49,67],"is":[50,112],"one":[51],"of":[52,62,88,97,118,131,144,176],"this":[53,72],"situation.":[54],"Furthermore,":[55,101],"an":[56],"imbalance":[57],"quality":[59],"amount":[61],"recorded":[64],"by":[65,186],"severe":[69],"challenges.":[70,82],"paper,":[73],"we":[74,85],"introduce":[75],"two":[76],"calibration":[77],"methods":[78],"tackle":[80],"these":[81],"particular,":[84],"applied":[86],"scaling":[87],"the":[89,98,105,116,119,129,141,171,177,183],"features":[90],"deal":[92],"varying":[94],"frequency":[95],"response":[96],"devices.":[100],"account":[103],"for":[104,160],"distribution,":[108],"heated-up":[110,132],"softmax":[111],"embedded":[113],"calibrate":[115],"predictions":[117],"model.":[120],"We":[121],"use":[122],"robust":[123],"resource-efficient":[125],"models,":[126],"show":[128],"efficiency":[130],"softmax.":[133],"Our":[134],"ASC":[135],"system":[136,175,185],"reaches":[137],"state-of-the-art":[138],"performance":[139],"on":[140,168],"development":[142],"set":[143],"DCASE":[145,178],"challenge":[146,180],"2019":[147,179],"task":[148],"1B":[149],"only":[151],"~70K":[152],"parameters.":[153],"It":[154,166],"achieves":[155],"70.1%":[156],"average":[157],"accuracy":[159],"device":[161,164],"B":[162],"C.":[165],"performs":[167],"par":[169],"best":[172],"single":[173],"model":[174],"outperforms":[182],"baseline":[184],"28.7%":[187],"(absolute).":[188]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
