{"id":"https://openalex.org/W3015884429","doi":"https://doi.org/10.1109/icassp40776.2020.9053192","title":"Speech Emotion Recognition with Local-Global Aware Deep Representation Learning","display_name":"Speech Emotion Recognition with Local-Global Aware Deep Representation Learning","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015884429","doi":"https://doi.org/10.1109/icassp40776.2020.9053192","mag":"3015884429"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053192","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/A5107933093","display_name":"Jiaxing Liu","orcid":"https://orcid.org/0009-0002-0832-4985"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaxing Liu","raw_affiliation_strings":["Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055459279","display_name":"Zhilei Liu","orcid":"https://orcid.org/0000-0003-1447-6256"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhilei Liu","raw_affiliation_strings":["Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101745213","display_name":"Longbiao Wang","orcid":"https://orcid.org/0000-0002-8094-6861"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longbiao Wang","raw_affiliation_strings":["Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055229622","display_name":"Lili Guo","orcid":"https://orcid.org/0000-0002-5526-0980"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lili Guo","raw_affiliation_strings":["Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017251198","display_name":"Jianwu Dang","orcid":"https://orcid.org/0000-0002-9237-4821"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianwu Dang","raw_affiliation_strings":["Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5107933093"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":6.1505,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":{"value":0.96807457,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"7174","last_page":"7178"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9994000196456909,"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/T11309","display_name":"Music and Audio Processing","score":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7860535383224487},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7471863627433777},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.745820939540863},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6054577827453613},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.5558491945266724},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5058960318565369},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5021884441375732},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4903731346130371},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.43928173184394836},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40472662448883057},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32150185108184814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7860535383224487},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7471863627433777},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.745820939540863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6054577827453613},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.5558491945266724},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5058960318565369},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5021884441375732},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4903731346130371},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.43928173184394836},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40472662448883057},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32150185108184814},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053192","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1963552095","https://openalex.org/W2080576537","https://openalex.org/W2105768069","https://openalex.org/W2137129454","https://openalex.org/W2146334809","https://openalex.org/W2161073241","https://openalex.org/W2295001676","https://openalex.org/W2312140198","https://openalex.org/W2399733683","https://openalex.org/W2408520939","https://openalex.org/W2648194195","https://openalex.org/W2747664154","https://openalex.org/W2796138868","https://openalex.org/W2800253600","https://openalex.org/W2885005742","https://openalex.org/W2889107526","https://openalex.org/W2889325879","https://openalex.org/W2889374687","https://openalex.org/W2897402719","https://openalex.org/W2962853356","https://openalex.org/W2963403868","https://openalex.org/W2963703618","https://openalex.org/W2964318666","https://openalex.org/W4295238618","https://openalex.org/W4385245566","https://openalex.org/W6680189088","https://openalex.org/W6697498398","https://openalex.org/W6714031499","https://openalex.org/W6739901393","https://openalex.org/W6743446608","https://openalex.org/W6751741970"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W3116150086","https://openalex.org/W2999805992","https://openalex.org/W4291897433","https://openalex.org/W3011074480","https://openalex.org/W2936488316"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"network":[2,33],"(CNN)":[3],"based":[4],"deep":[5,57,68,110],"representation":[6,69],"learning":[7,70],"methods":[8],"for":[9],"speech":[10],"emotion":[11],"recognition":[12],"(SER)":[13],"have":[14],"demonstrated":[15],"great":[16],"success.":[17],"The":[18,128],"basic":[19],"design":[20],"of":[21,39,103,143],"CNN":[22,85],"restricts":[23],"the":[24,37,43,48,54,89,93,136],"ability":[25],"to":[26,41,87,106,135],"model":[27],"only":[28],"local":[29,55,90,129],"information":[30],"well.":[31],"Capsule":[32],"(CapsNet)":[34],"can":[35],"overcome":[36],"shortages":[38],"CNNs":[40],"capture":[42],"shallow":[44,108],"global":[45,58,111,131],"features":[46],"from":[47],"spectrogram,":[49],"although":[50],"CapsNet":[51,121],"cannot":[52],"learn":[53,88,107],"and":[56,109,130,138],"information.":[59,112],"In":[60,92],"this":[61,116],"paper,":[62],"we":[63,96],"propose":[64],"a":[65,80,98,119,124],"local-global":[66],"aware":[67],"system":[71],"that":[72],"mainly":[73],"includes":[74],"two":[75],"modules.":[76],"One":[77],"module":[78],"contains":[79],"multi-scale":[81],"CNN,":[82],"time-":[83],"frequency":[84],"(TFCNN)":[86],"representation.":[91],"other":[94],"module,":[95],"introduce":[97],"structure":[99,117],"with":[100],"dense":[101],"connections":[102],"multiple":[104],"blocks":[105],"Every":[113],"block":[114],"in":[115],"is":[118],"complete":[120],"improved":[122],"by":[123],"new":[125],"routing":[126],"algorithm.":[127],"representations":[132],"are":[133],"fed":[134],"classifier":[137],"achieve":[139],"an":[140],"absolute":[141],"increase":[142],"at":[144],"least":[145],"4.25%":[146],"than":[147],"benchmarks":[148],"on":[149],"IEMOCAP.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}