{"id":"https://openalex.org/W4225265481","doi":"https://doi.org/10.1109/icassp43922.2022.9746909","title":"A Commonsense Knowledge Enhanced Network with Retrospective Loss for Emotion Recognition in Spoken Dialog","display_name":"A Commonsense Knowledge Enhanced Network with Retrospective Loss for Emotion Recognition in Spoken Dialog","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4225265481","doi":"https://doi.org/10.1109/icassp43922.2022.9746909"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9746909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746909","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5101064051","display_name":"Yunhe Xie","orcid":"https://orcid.org/0000-0002-9597-7476"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhe Xie","raw_affiliation_strings":["Harbin Institute of Technology,Faculty of Computing,China","Faculty of Computing, Harbin Institute of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Faculty of Computing,China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"Faculty of Computing, Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033705258","display_name":"Chengjie Sun","orcid":"https://orcid.org/0000-0001-9081-1410"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengjie Sun","raw_affiliation_strings":["Harbin Institute of Technology,Faculty of Computing,China","Faculty of Computing, Harbin Institute of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Faculty of Computing,China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"Faculty of Computing, Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062481072","display_name":"Zhenzhou Ji","orcid":"https://orcid.org/0000-0001-6686-3819"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenzhou Ji","raw_affiliation_strings":["Harbin Institute of Technology,Faculty of Computing,China","Faculty of Computing, Harbin Institute of Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Faculty of Computing,China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"Faculty of Computing, Harbin Institute of Technology, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"7027","last_page":"7031"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9958999752998352,"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"}},{"id":"https://openalex.org/T10709","display_name":"Social Robot Interaction and HRI","score":0.9861000180244446,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dialog-box","display_name":"Dialog box","score":0.8646347522735596},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7337127923965454},{"id":"https://openalex.org/keywords/commonsense-knowledge","display_name":"Commonsense knowledge","score":0.6921744346618652},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6209484934806824},{"id":"https://openalex.org/keywords/commonsense-reasoning","display_name":"Commonsense reasoning","score":0.5074133276939392},{"id":"https://openalex.org/keywords/dialog-system","display_name":"Dialog system","score":0.498917818069458},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48216885328292847},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4197949767112732},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.1802920699119568},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.15030035376548767}],"concepts":[{"id":"https://openalex.org/C173853756","wikidata":"https://www.wikidata.org/wiki/Q86915","display_name":"Dialog box","level":2,"score":0.8646347522735596},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7337127923965454},{"id":"https://openalex.org/C30542707","wikidata":"https://www.wikidata.org/wiki/Q1603203","display_name":"Commonsense knowledge","level":3,"score":0.6921744346618652},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6209484934806824},{"id":"https://openalex.org/C193221554","wikidata":"https://www.wikidata.org/wiki/Q5153664","display_name":"Commonsense reasoning","level":2,"score":0.5074133276939392},{"id":"https://openalex.org/C190954187","wikidata":"https://www.wikidata.org/wiki/Q5270587","display_name":"Dialog system","level":3,"score":0.498917818069458},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48216885328292847},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4197949767112732},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1802920699119568},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.15030035376548767}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp43922.2022.9746909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746909","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 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":22,"referenced_works":["https://openalex.org/W2146334809","https://openalex.org/W2561529111","https://openalex.org/W2740550900","https://openalex.org/W2805662932","https://openalex.org/W2891359673","https://openalex.org/W2939987519","https://openalex.org/W2963686995","https://openalex.org/W2964300796","https://openalex.org/W2965453734","https://openalex.org/W2982248052","https://openalex.org/W2996849360","https://openalex.org/W3012159372","https://openalex.org/W3012721484","https://openalex.org/W3016232306","https://openalex.org/W3039444588","https://openalex.org/W3080441097","https://openalex.org/W3092695663","https://openalex.org/W3102233600","https://openalex.org/W3160183718","https://openalex.org/W3173751215","https://openalex.org/W3174683006","https://openalex.org/W6766310171"],"related_works":["https://openalex.org/W48079147","https://openalex.org/W2394821827","https://openalex.org/W2563921006","https://openalex.org/W1963944933","https://openalex.org/W1600043506","https://openalex.org/W2111550420","https://openalex.org/W3035583586","https://openalex.org/W2549666521","https://openalex.org/W4320165839","https://openalex.org/W3133893348"],"abstract_inverted_index":{"The":[0],"recent":[1],"surges":[2],"in":[3,11,79],"the":[4,20,26,31,87,99,111,132,142,146],"open":[5],"conversational":[6],"data":[7],"caused":[8],"Emotion":[9],"Recognition":[10],"Spoken":[12],"Dialog":[13],"(ERSD)":[14],"to":[15,38,57,76,93,109,131],"gain":[16],"much":[17],"attention.":[18],"However,":[19],"existing":[21],"ERSD":[22],"datasets\u2019":[23],"scale":[24],"limits":[25],"model\u2019s":[27,112],"complete":[28],"reasoning.":[29,102],"Moreover,":[30],"artificial":[32],"dialogue":[33,41],"agent":[34],"is":[35,91,107,128],"ideally":[36],"able":[37],"reference":[39],"past":[40],"experiences.":[42],"This":[43],"paper":[44],"proposes":[45],"a":[46,52,73,104],"Commonsense":[47],"Knowledge":[48],"Enhanced":[49],"Network":[50],"with":[51],"retrospective":[53,105],"loss,":[54],"namely":[55],"CKE-Net,":[56],"hierarchically":[58],"perform":[59],"dialog":[60],"modeling,":[61],"external":[62],"knowledge":[63],"integration,":[64],"and":[65,120],"historical":[66],"state":[67],"retrospect.":[68],"Specifically,":[69],"we":[70],"first":[71],"adopt":[72],"transformer-based":[74],"encoder":[75],"model":[77,140],"context":[78],"multi-view":[80],"by":[81],"elaborating":[82],"different":[83],"mask":[84],"matrices.":[85],"Then,":[86],"graph":[88],"attention":[89],"network":[90],"used":[92],"introduce":[94],"commonsense":[95],"knowledge,":[96],"which":[97],"benefits":[98],"complex":[100],"emotional":[101],"Finally,":[103],"loss":[106],"added":[108],"utilize":[110],"prior":[113],"experience":[114],"during":[115],"training.":[116],"Experiments":[117],"on":[118],"IEMOCAP":[119],"MELD":[121],"datasets":[122],"demonstrate":[123],"that":[124,138],"every":[125],"designed":[126],"module":[127],"consistently":[129],"beneficial":[130],"performance.":[133],"Extensive":[134],"experimental":[135],"results":[136],"show":[137],"our":[139],"outperforms":[141],"state-of-the-art":[143],"models":[144],"across":[145],"two":[147],"benchmark":[148],"datasets.":[149]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
