{"id":"https://openalex.org/W2997424368","doi":"https://doi.org/10.1109/icct46805.2019.8947252","title":"Robust Deep Feature Extraction Method for Acoustic Scene Classification","display_name":"Robust Deep Feature Extraction Method for Acoustic Scene Classification","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2997424368","doi":"https://doi.org/10.1109/icct46805.2019.8947252","mag":"2997424368"},"language":"en","primary_location":{"id":"doi:10.1109/icct46805.2019.8947252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icct46805.2019.8947252","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","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/A5020082230","display_name":"Kun Yao","orcid":"https://orcid.org/0000-0001-9113-6437"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kun Yao","raw_affiliation_strings":["Army Engineering University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Army Engineering University, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024997158","display_name":"Jibin Yang","orcid":"https://orcid.org/0000-0002-1072-5422"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jibin Yang","raw_affiliation_strings":["Army Engineering University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Army Engineering University, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011581435","display_name":"Xiongwei Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiongwei Zhang","raw_affiliation_strings":["Army Engineering University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Army Engineering University, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086000146","display_name":"Changyan Zheng","orcid":"https://orcid.org/0000-0002-2088-9308"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changyan Zheng","raw_affiliation_strings":["Army Engineering University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Army Engineering University, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090288019","display_name":"Xin Zeng","orcid":"https://orcid.org/0000-0001-9948-2772"},"institutions":[{"id":"https://openalex.org/I4210163363","display_name":"PLA Army Engineering University","ror":"https://ror.org/05mgp8x93","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163363"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Zeng","raw_affiliation_strings":["Army Engineering University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Army Engineering University, Nanjing, China","institution_ids":["https://openalex.org/I4210163363"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5020082230"],"corresponding_institution_ids":["https://openalex.org/I4210163363"],"apc_list":null,"apc_paid":null,"fwci":0.6634,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.70166933,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"198","last_page":"202"},"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":0.9897000193595886,"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":0.9531872272491455},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7861593961715698},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7685186862945557},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7440711259841919},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.682165265083313},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6414160132408142},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5878975987434387},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5699835419654846},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5266449451446533},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5001060962677002},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4458141624927521},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18913891911506653},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.15008938312530518}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9531872272491455},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7861593961715698},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7685186862945557},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7440711259841919},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.682165265083313},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6414160132408142},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5878975987434387},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5699835419654846},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5266449451446533},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5001060962677002},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4458141624927521},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18913891911506653},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.15008938312530518},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icct46805.2019.8947252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icct46805.2019.8947252","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","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":32,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1972567154","https://openalex.org/W2052666245","https://openalex.org/W2052958516","https://openalex.org/W2095705004","https://openalex.org/W2096733369","https://openalex.org/W2145287260","https://openalex.org/W2183341477","https://openalex.org/W2593451766","https://openalex.org/W2735553491","https://openalex.org/W2751841560","https://openalex.org/W2766087987","https://openalex.org/W2768083292","https://openalex.org/W2768188490","https://openalex.org/W2784163702","https://openalex.org/W2949117887","https://openalex.org/W2962793908","https://openalex.org/W2963466847","https://openalex.org/W2963656735","https://openalex.org/W2964328535","https://openalex.org/W2969985801","https://openalex.org/W3005025755","https://openalex.org/W3099206234","https://openalex.org/W3103152812","https://openalex.org/W4293665662","https://openalex.org/W6638667902","https://openalex.org/W6674330103","https://openalex.org/W6729831399","https://openalex.org/W6735013348","https://openalex.org/W6745930336","https://openalex.org/W6748010250","https://openalex.org/W6773273899"],"related_works":["https://openalex.org/W2982889384","https://openalex.org/W4226227567","https://openalex.org/W2971218105","https://openalex.org/W4287113729","https://openalex.org/W3173314472","https://openalex.org/W3103152812","https://openalex.org/W4300326282","https://openalex.org/W2742395793","https://openalex.org/W2997424368","https://openalex.org/W2810018382"],"abstract_inverted_index":{"In":[0,17],"recent":[1],"years,":[2],"increasing":[3],"number":[4],"of":[5,22,38,48,56,62,84],"acoustic":[6,39,43],"scene":[7,44],"classification":[8,32,111],"(ASC)":[9],"methods":[10],"are":[11,113],"based":[12,98],"on":[13,30,99,121],"deep":[14,24,76,96,101],"learning":[15,74],"models.":[16],"these":[18],"models,":[19],"the":[20,31,35,49,54,60,66,71,82,88,109,116],"extraction":[21],"robust":[23],"feature":[25,63,77,97],"plays":[26],"an":[27,42],"important":[28],"role":[29],"accuracy.":[33],"However":[34],"complex":[36],"combination":[37],"phenomena":[40],"in":[41,46],"results":[45,112],"overlapping":[47],"analysis":[50],"features,":[51],"which":[52,119,126],"degrades":[53],"performance":[55],"ASC.":[57],"To":[58],"enhance":[59],"compactness":[61],"and":[64,87],"fit":[65],"multi-classification":[67],"task,":[68],"we":[69,80],"explored":[70],"data":[72],"label":[73,85],"for":[75],"extraction.":[78],"And":[79],"combined":[81],"method":[83],"smoothing(LS)":[86],"additive":[89],"margin":[90],"softmax":[91],"loss":[92],"(AM-softmax)":[93],"to":[94],"extract":[95],"VGG-style":[100],"neural":[102],"network.":[103],"The":[104],"comparison":[105],"experiments":[106],"show":[107],"that":[108],"best":[110],"obtained":[114],"by":[115],"proposed":[117],"method,":[118],"accuracy":[120],"ESC-50":[122],"dataset":[123],"is":[124,127],"81.9%,":[125],"beyond":[128],"human":[129],"performance.":[130]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
