{"id":"https://openalex.org/W3015530480","doi":"https://doi.org/10.1109/icassp40776.2020.9053274","title":"Acoustic Scene Classification Using Deep Residual Networks with Late Fusion of Separated High and Low Frequency Paths","display_name":"Acoustic Scene Classification Using Deep Residual Networks with Late Fusion of Separated High and Low Frequency Paths","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015530480","doi":"https://doi.org/10.1109/icassp40776.2020.9053274","mag":"3015530480"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053274","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053274","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/A5000677611","display_name":"Mark D. McDonnell","orcid":"https://orcid.org/0000-0002-7009-3869"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Mark D. McDonnell","raw_affiliation_strings":["Computational Learning Systems Laboratory, School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA, Australia"],"affiliations":[{"raw_affiliation_string":"Computational Learning Systems Laboratory, School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA, Australia","institution_ids":["https://openalex.org/I170239107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084132742","display_name":"Wei Gao","orcid":"https://orcid.org/0000-0002-0140-7561"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wei Gao","raw_affiliation_strings":["Computational Learning Systems Laboratory, School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA, Australia"],"affiliations":[{"raw_affiliation_string":"Computational Learning Systems Laboratory, School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, SA, Australia","institution_ids":["https://openalex.org/I170239107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000677611"],"corresponding_institution_ids":["https://openalex.org/I170239107"],"apc_list":null,"apc_paid":null,"fwci":11.6681,"has_fulltext":false,"cited_by_count":100,"citation_normalized_percentile":{"value":0.99163924,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"141","last_page":"145"},"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":0.9983999729156494,"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/T11665","display_name":"Animal Vocal Communication and Behavior","score":0.9767000079154968,"subfield":{"id":"https://openalex.org/subfields/1309","display_name":"Developmental Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.8918700814247131},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7588762044906616},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7271421551704407},{"id":"https://openalex.org/keywords/binaural-recording","display_name":"Binaural recording","score":0.675794243812561},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5437061786651611},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5341552495956421},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5203254222869873},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5043696165084839},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4769816994667053},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.46375659108161926},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.44832438230514526},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.14564773440361023},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11749476194381714},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10235920548439026},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09357753396034241}],"concepts":[{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.8918700814247131},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7588762044906616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7271421551704407},{"id":"https://openalex.org/C201247586","wikidata":"https://www.wikidata.org/wiki/Q5612967","display_name":"Binaural recording","level":2,"score":0.675794243812561},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5437061786651611},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5341552495956421},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5203254222869873},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5043696165084839},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4769816994667053},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.46375659108161926},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.44832438230514526},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.14564773440361023},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11749476194381714},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10235920548439026},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09357753396034241},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053274","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053274","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2086384421","https://openalex.org/W2302255633","https://openalex.org/W2765407302","https://openalex.org/W2962703323","https://openalex.org/W2962711843","https://openalex.org/W2963263347","https://openalex.org/W2963403664","https://openalex.org/W4289465850","https://openalex.org/W4295723153","https://openalex.org/W6698183232","https://openalex.org/W6745136726","https://openalex.org/W6748713063","https://openalex.org/W6752516136","https://openalex.org/W6756022612"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W2011227383","https://openalex.org/W2088854863","https://openalex.org/W3179495260","https://openalex.org/W1976719989","https://openalex.org/W2942893872","https://openalex.org/W3127543252","https://openalex.org/W2065606036","https://openalex.org/W2016904525"],"abstract_inverted_index":{"We":[0,23,74,109],"investigate":[1],"the":[2,25,32,50,71,87,99,111,120,145,169,173],"problem":[3],"of":[4,113,122,132,139,183],"acoustic":[5,84],"scene":[6,85],"classification,":[7],"using":[8,77],"a":[9,95,180,190],"deep":[10],"residual":[11,51],"network":[12,26,72],"applied":[13],"to":[14,27,70,152,194],"log-mel":[15,19,123],"spectrograms":[16,38],"complemented":[17],"by":[18,94,119],"deltas":[20],"and":[21,34,57,98,125,172],"delta-deltas.":[22],"design":[24],"take":[28],"into":[29],"account":[30],"that":[31,62,126],"temporal":[33],"frequency":[35],"axes":[36],"in":[37,49,162],"represent":[39],"fundamentally":[40],"different":[41],"information.":[42],"In":[43,155],"particular,":[44,156],"we":[45],"use":[46,121,138],"two":[47,66,78],"pathways":[48],"network:":[52],"one":[53,58],"for":[54,59,83],"high":[55],"frequencies":[56],"low":[60],"frequencies,":[61],"were":[63],"fused":[64],"just":[65],"convolutional":[67],"layers":[68],"prior":[69],"output.":[73],"conduct":[75],"experiments":[76],"public":[79],"2019":[80,163],"DCASE":[81,164],"datasets":[82],"classification;":[86],"first":[88],"with":[89,101,149],"binaural":[90],"audio":[91,103],"inputs":[92,104],"recorded":[93,105],"single":[96,135],"device,":[97],"second":[100,160],"single-channel":[102],"through":[106],"various":[107],"devices.":[108,154],"show":[110],"performance":[112],"our":[114,128,157],"models":[115],"are":[116],"significantly":[117],"enhanced":[118],"deltas,":[124],"overall":[127],"approach":[129,158],"is":[130],"capable":[131],"training":[133,197],"strong":[134],"models,":[136],"without":[137],"any":[140,196],"supplementary":[141],"data":[142,188],"from":[143,189],"outside":[144],"official":[146],"challenge":[147],"dataset,":[148],"excellent":[150],"generalization":[151],"unknown":[153],"achieved":[159],"place":[161],"Task":[165,175],"1b":[166],"(0.4%":[167],"behind":[168],"winning":[170],"entry),":[171],"best":[174],"1B":[176],"evaluation":[177],"results":[178],"(by":[179],"large":[181],"margin":[182],"over":[184],"5%)":[185],"on":[186],"test":[187],"device":[191],"not":[192],"used":[193],"record":[195],"data.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":40},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2026-01-25T23:04:38.658462","created_date":"2025-10-10T00:00:00"}
