{"id":"https://openalex.org/W4224217547","doi":"https://doi.org/10.1145/3523181.3523195","title":"KL Divergence Adaptive Weight Combination Multi-Classifier Emotion Recognition Method Fused with Bimodality","display_name":"KL Divergence Adaptive Weight Combination Multi-Classifier Emotion Recognition Method Fused with Bimodality","publication_year":2022,"publication_date":"2022-02-24","ids":{"openalex":"https://openalex.org/W4224217547","doi":"https://doi.org/10.1145/3523181.3523195"},"language":"en","primary_location":{"id":"doi:10.1145/3523181.3523195","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523181.3523195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 3rd Asia Service Sciences and Software Engineering Conference","raw_type":"proceedings-article"},"type":"conference-paper","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/A5031600874","display_name":"Xi Bin Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210122543","display_name":"Guangdong Polytechnic Normal University","ror":"https://ror.org/02pcb5m77","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210122543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Bin Xu","raw_affiliation_strings":["Guangdong Engineering Polytechnic, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Engineering Polytechnic, China","institution_ids":["https://openalex.org/I4210122543"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110442962","display_name":"Xiao Lei Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210156464","display_name":"Anhui Xinhua University","ror":"https://ror.org/053d7x641","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210156464"]},{"id":"https://openalex.org/I4400573165","display_name":"Guangzhou Xinhua University","ror":"https://ror.org/0068n3903","country_code":null,"type":"education","lineage":["https://openalex.org/I4400573165"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Lei Zhao","raw_affiliation_strings":["Guangzhou Xinhua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou Xinhua University, China","institution_ids":["https://openalex.org/I4210156464","https://openalex.org/I4400573165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047211283","display_name":"Guang Qin Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I4400600917","display_name":"Guangzhou College of Commerce","ror":"https://ror.org/04f0j5d06","country_code":null,"type":"education","lineage":["https://openalex.org/I4400600917"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guang Qin Wang","raw_affiliation_strings":["Guangzhou College of Commerce, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou College of Commerce, China","institution_ids":["https://openalex.org/I4400600917"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2018","issue":null,"first_page":"95","last_page":"101"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.7208999991416931,"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":0.7208999991416931,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.629800021648407,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.5906999707221985,"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/computer-science","display_name":"Computer science","score":0.7255576848983765},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.6243523359298706},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6165755987167358},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5955398678779602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5798770189285278},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.554741382598877},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.48841947317123413},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48294228315353394},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.459215372800827},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4408474862575531}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7255576848983765},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.6243523359298706},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6165755987167358},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5955398678779602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5798770189285278},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.554741382598877},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.48841947317123413},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48294228315353394},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.459215372800827},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4408474862575531},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3523181.3523195","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3523181.3523195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 3rd Asia Service Sciences and Software Engineering Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.4399999976158142,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2441515906","https://openalex.org/W2899605173","https://openalex.org/W4285750789","https://openalex.org/W4324085337"],"related_works":["https://openalex.org/W2185469136","https://openalex.org/W2011264131","https://openalex.org/W4306353150","https://openalex.org/W2026860389","https://openalex.org/W8219677","https://openalex.org/W3216879894","https://openalex.org/W4301143707","https://openalex.org/W2952745240","https://openalex.org/W3105646692","https://openalex.org/W4387914125"],"abstract_inverted_index":{"There":[0],"is":[1,13,18],"the":[2,24,35,44,51,54,56,69,73,75,88,92,96,100,104,110,119,134,142,150,155,161],"problem":[3],"that":[4,154],"single":[5,8],"modal":[6],"and":[7,16,26,34,98,149],"classifier":[9,131],"emotion":[10,145,162],"recognition":[11,45,111,136,163],"rate":[12],"not":[14,19],"high":[15],"robustness":[17],"strong.":[20],"In":[21,47,64],"this":[22],"paper,":[23],"text":[25],"speech":[27],"easily":[28],"available":[29],"dual":[30],"modalities":[31,93],"were":[32],"combined,":[33],"combined":[36],"multi-classifier":[37],"strategy":[38],"was":[39,126,139],"used":[40,127],"to":[41,49,66,86,94,128,132],"further":[42,67],"improve":[43,160],"rate.":[46,164],"order":[48,65],"reduce":[50],"complexity":[52],"of":[53,81],"model,":[55],"bimodal":[57,76,82,105],"features":[58,77,106],"adopt":[59],"distinguishing":[60],"manual":[61],"extraction":[62],"method.":[63],"strengthen":[68,95],"complementary":[70],"advantages":[71],"between":[72,91],"modalities,":[74],"undergo":[78],"a":[79],"layer":[80],"interactive":[83],"attention":[84],"processing":[85],"remove":[87],"negative":[89],"interference":[90],"connection":[97],"retain":[99],"common":[101],"features.":[102],"Then":[103],"are":[107,113],"cascaded.":[108],"And":[109],"results":[112,152],"obtained":[114],"through":[115],"different":[116],"classifiers.":[117],"Finally,":[118],"KL":[120],"divergence":[121],"adaptive":[122],"weight":[123],"fusion":[124],"method":[125,157],"combine":[129],"each":[130],"obtain":[133],"final":[135],"result.":[137],"It":[138],"verified":[140],"on":[141],"IEMOCAP":[143],"multi-modal":[144],"detection":[146],"data":[147],"set,":[148],"experimental":[151],"show":[153],"proposed":[156],"can":[158],"significantly":[159]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}