{"id":"https://openalex.org/W3190674349","doi":"https://doi.org/10.1109/acii52823.2021.9597390","title":"Using Knowledge-Embedded Attention to Augment Pre-trained Language Models for Fine-Grained Emotion Recognition","display_name":"Using Knowledge-Embedded Attention to Augment Pre-trained Language Models for Fine-Grained Emotion Recognition","publication_year":2021,"publication_date":"2021-09-28","ids":{"openalex":"https://openalex.org/W3190674349","doi":"https://doi.org/10.1109/acii52823.2021.9597390","mag":"3190674349"},"language":"en","primary_location":{"id":"doi:10.1109/acii52823.2021.9597390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acii52823.2021.9597390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2108.00194","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073103551","display_name":"Varsha Suresh","orcid":"https://orcid.org/0000-0001-9872-5832"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Varsha Suresh","raw_affiliation_strings":["Department of Computer Science, National University of Singapore","National University of Singapore,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, National University of Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"National University of Singapore,","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009199818","display_name":"Desmond C. Ong","orcid":"https://orcid.org/0000-0002-6781-8072"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]},{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]},{"id":"https://openalex.org/I3004594783","display_name":"Institute of High Performance Computing","ror":"https://ror.org/02n0ejh50","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I3004594783","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Desmond C. Ong","raw_affiliation_strings":["Department of Information Systems and Analytics, National University of Singapore","Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore","National University of Singapore,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Systems and Analytics, National University of Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore","institution_ids":["https://openalex.org/I115228651","https://openalex.org/I3004594783"]},{"raw_affiliation_string":"National University of Singapore,","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09509258,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9980999827384949,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9980999827384949,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9977999925613403,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9965999722480774,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/augment","display_name":"Augment","score":0.6166306138038635},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6034471988677979},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.5769514441490173},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5576815605163574},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.43587642908096313},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40290340781211853},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3920947313308716},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3523974120616913},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.16801410913467407}],"concepts":[{"id":"https://openalex.org/C2779070825","wikidata":"https://www.wikidata.org/wiki/Q760434","display_name":"Augment","level":2,"score":0.6166306138038635},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6034471988677979},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.5769514441490173},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5576815605163574},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.43587642908096313},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40290340781211853},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3920947313308716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3523974120616913},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.16801410913467407},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/acii52823.2021.9597390","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acii52823.2021.9597390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2108.00194","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2108.00194","pdf_url":"https://arxiv.org/pdf/2108.00194","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3190674349","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2108.00194","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2108.00194","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2108.00194","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2108.00194","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2108.00194","pdf_url":"https://arxiv.org/pdf/2108.00194","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5799999833106995,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320311649","display_name":"Ministry of Education","ror":"https://ror.org/036nq5137"},{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W1893417051","https://openalex.org/W1985918513","https://openalex.org/W1994198923","https://openalex.org/W2091084672","https://openalex.org/W2265846598","https://openalex.org/W2597655663","https://openalex.org/W2626778328","https://openalex.org/W2740550900","https://openalex.org/W2752234108","https://openalex.org/W2790309729","https://openalex.org/W2791393728","https://openalex.org/W2791506524","https://openalex.org/W2798357113","https://openalex.org/W2806227953","https://openalex.org/W2894248579","https://openalex.org/W2912483755","https://openalex.org/W2949778647","https://openalex.org/W2951583236","https://openalex.org/W2953356739","https://openalex.org/W2962824509","https://openalex.org/W2963341956","https://openalex.org/W2963712766","https://openalex.org/W2963873807","https://openalex.org/W2964099336","https://openalex.org/W2964121744","https://openalex.org/W2964207259","https://openalex.org/W2968289784","https://openalex.org/W2969138254","https://openalex.org/W2970431814","https://openalex.org/W2974884974","https://openalex.org/W2990568760","https://openalex.org/W2990881710","https://openalex.org/W2996035354","https://openalex.org/W2996229676","https://openalex.org/W2996849360","https://openalex.org/W3005441132","https://openalex.org/W3012159372","https://openalex.org/W3015322406","https://openalex.org/W3034323190","https://openalex.org/W3035153870","https://openalex.org/W3035419191","https://openalex.org/W3041387857","https://openalex.org/W3100283070","https://openalex.org/W3105111366","https://openalex.org/W3106255016","https://openalex.org/W3116718057","https://openalex.org/W3173541742","https://openalex.org/W3176750236","https://openalex.org/W3213528755","https://openalex.org/W4251591997","https://openalex.org/W6631190155","https://openalex.org/W6730529904","https://openalex.org/W6735377749","https://openalex.org/W6737061669","https://openalex.org/W6739901393","https://openalex.org/W6751820410","https://openalex.org/W6755207826","https://openalex.org/W6768179808","https://openalex.org/W6771101304","https://openalex.org/W6771917389","https://openalex.org/W6773813506"],"related_works":["https://openalex.org/W2571740133","https://openalex.org/W3161446961","https://openalex.org/W3204451724","https://openalex.org/W3173765582","https://openalex.org/W2796140931","https://openalex.org/W3174466756","https://openalex.org/W3115807082","https://openalex.org/W3198720169","https://openalex.org/W3134548317","https://openalex.org/W3022202212","https://openalex.org/W3111795671","https://openalex.org/W2980463662","https://openalex.org/W2469126441","https://openalex.org/W2739474071","https://openalex.org/W3042803450","https://openalex.org/W3207833857","https://openalex.org/W2891575196","https://openalex.org/W2740693122","https://openalex.org/W2940749459","https://openalex.org/W2625435062"],"abstract_inverted_index":{"Modern":[0],"emotion":[1,45,59,79],"recognition":[2,60],"systems":[3],"are":[4],"trained":[5],"to":[6,17,33,42,75,81,107],"recognize":[7],"only":[8],"a":[9,66],"small":[10],"set":[11],"of":[12,22],"emotions,":[13,110],"and":[14,26,89,94,103,114],"hence":[15],"fail":[16],"capture":[18],"the":[19,83],"broad":[20],"spectrum":[21],"emotions":[23],"people":[24],"experience":[25],"express":[27],"in":[28,35],"daily":[29],"life.":[30],"In":[31],"order":[32],"engage":[34],"more":[36,50],"empathetic":[37],"interactions,":[38],"future":[39],"AI":[40],"has":[41],"perform":[43],"fine-grained":[44,58],"recognition,":[46],"distinguishing":[47],"between":[48],"many":[49],"varied":[51],"emotions.":[52],"Here,":[53],"we":[54],"focus":[55],"on":[56,100],"improving":[57],"by":[61],"introducing":[62],"external":[63],"knowledge":[64,77],"into":[65],"pre-trained":[67,87],"self-attention":[68],"model.":[69],"We":[70],"propose":[71],"Knowledge-Embedded":[72],"Attention":[73],"(KEA)":[74],"use":[76],"from":[78,86],"lexicons":[80],"augment":[82],"contextual":[84],"representations":[85],"ELECTRA":[88],"BERT":[90],"models.":[91],"Our":[92],"results":[93],"error":[95],"analyses":[96],"outperform":[97],"previous":[98],"models":[99],"several":[101],"datasets,":[102],"is":[104],"better":[105],"able":[106],"differentiate":[108],"closely-confusable":[109],"such":[111],"as":[112],"afraid":[113],"terrified.":[115]},"counts_by_year":[],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}
