{"id":"https://openalex.org/W4309391683","doi":"https://doi.org/10.1109/taffc.2022.3221801","title":"Estimating the Uncertainty in Emotion Class Labels With Utterance-Specific Dirichlet Priors","display_name":"Estimating the Uncertainty in Emotion Class Labels With Utterance-Specific Dirichlet Priors","publication_year":2022,"publication_date":"2022-11-14","ids":{"openalex":"https://openalex.org/W4309391683","doi":"https://doi.org/10.1109/taffc.2022.3221801"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2022.3221801","is_oa":true,"landing_page_url":"https://doi.org/10.1109/taffc.2022.3221801","pdf_url":"https://ieeexplore.ieee.org/ielx7/5165369/5520654/09947288.pdf","source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/5165369/5520654/09947288.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079268196","display_name":"Wen Wu","orcid":"https://orcid.org/0000-0001-8116-7715"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wen Wu","raw_affiliation_strings":["Department of Engineering, University of Cambridge, Cambridge, U.K","Department of Engineering, University of Cambridge, Cambridge, England"],"raw_orcid":"https://orcid.org/0000-0001-8116-7715","affiliations":[{"raw_affiliation_string":"Department of Engineering, University of Cambridge, Cambridge, U.K","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"Department of Engineering, University of Cambridge, Cambridge, England","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100460206","display_name":"Chao Zhang","orcid":"https://orcid.org/0000-0002-7730-5131"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]},{"id":"https://openalex.org/I4210096386","display_name":"Bridge University","ror":"https://ror.org/00cbm0437","country_code":"SS","type":"education","lineage":["https://openalex.org/I4210096386"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN","GB","SS"],"is_corresponding":false,"raw_author_name":"Chao Zhang","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China","Cambridge University, Cambridge, England"],"raw_orcid":"https://orcid.org/0000-0002-7730-5131","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Cambridge University, Cambridge, England","institution_ids":["https://openalex.org/I241749","https://openalex.org/I4210096386"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025119324","display_name":"Xixin Wu","orcid":"https://orcid.org/0000-0001-9543-1572"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xixin Wu","raw_affiliation_strings":["Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Hong Kong","Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0001-9543-1572","affiliations":[{"raw_affiliation_string":"Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002191410","display_name":"Philip C. Woodland","orcid":"https://orcid.org/0000-0001-9069-0225"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Philip C. Woodland","raw_affiliation_strings":["Department of Engineering, University of Cambridge, Cambridge, U.K","Department of Engineering, University of Cambridge, Cambridge, England"],"raw_orcid":"https://orcid.org/0000-0001-9069-0225","affiliations":[{"raw_affiliation_string":"Department of Engineering, University of Cambridge, Cambridge, U.K","institution_ids":["https://openalex.org/I241749"]},{"raw_affiliation_string":"Department of Engineering, University of Cambridge, Cambridge, England","institution_ids":["https://openalex.org/I241749"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2763,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.82682225,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"14","issue":"4","first_page":"2810","last_page":"2822"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9954000115394592,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9954000115394592,"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":0.989799976348877,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9876000285148621,"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/prior-probability","display_name":"Prior probability","score":0.8200185298919678},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.8183255791664124},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6851096153259277},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.6792044639587402},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5182814002037048},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.4821562170982361},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43821603059768677},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4086931347846985},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40264463424682617},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3898332417011261},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.337583065032959},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.18206924200057983},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.14346373081207275}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.8200185298919678},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.8183255791664124},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6851096153259277},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.6792044639587402},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5182814002037048},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.4821562170982361},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43821603059768677},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4086931347846985},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40264463424682617},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3898332417011261},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.337583065032959},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.18206924200057983},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.14346373081207275},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taffc.2022.3221801","is_oa":true,"landing_page_url":"https://doi.org/10.1109/taffc.2022.3221801","pdf_url":"https://ieeexplore.ieee.org/ielx7/5165369/5520654/09947288.pdf","source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/taffc.2022.3221801","is_oa":true,"landing_page_url":"https://doi.org/10.1109/taffc.2022.3221801","pdf_url":"https://ieeexplore.ieee.org/ielx7/5165369/5520654/09947288.pdf","source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5699999928474426}],"awards":[{"id":"https://openalex.org/G380673404","display_name":"CAREER: Advanced Knowledge Extraction of Affective Behaviors During Natural Human Interaction","funder_award_id":"1453781","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5044766248","display_name":null,"funder_award_id":"grant EP/T022159/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G581313191","display_name":null,"funder_award_id":"EP/T022159/","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G5973173752","display_name":"CRI: CI-P: Creating the Largest Speech Emotional Database by Leveraging Existing Naturalistic Recordings","funder_award_id":"1823166","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7002347110","display_name":"Cambridge Service for Data Driven Discovery (CSD3) - A National Data Intensive Science Cloud for Converged Simulation, AI & Analytics","funder_award_id":"EP/T022159/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8080363172","display_name":null,"funder_award_id":"CNS-1823166","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320320273","display_name":"University of Cambridge","ror":"https://ror.org/013meh722"},{"id":"https://openalex.org/F4320321848","display_name":"Cambridge Trust","ror":"https://ror.org/05sprqy15"},{"id":"https://openalex.org/F4320327708","display_name":"University of Texas at Dallas","ror":"https://ror.org/049emcs32"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4309391683.pdf","grobid_xml":"https://content.openalex.org/works/W4309391683.grobid-xml"},"referenced_works_count":69,"referenced_works":["https://openalex.org/W99485238","https://openalex.org/W141927798","https://openalex.org/W175750906","https://openalex.org/W1494198834","https://openalex.org/W1932198206","https://openalex.org/W1965069145","https://openalex.org/W1986101067","https://openalex.org/W2009059481","https://openalex.org/W2045528981","https://openalex.org/W2046999604","https://openalex.org/W2058787788","https://openalex.org/W2085628288","https://openalex.org/W2146334809","https://openalex.org/W2147863532","https://openalex.org/W2149628368","https://openalex.org/W2156146072","https://openalex.org/W2158630797","https://openalex.org/W2170876097","https://openalex.org/W2183341477","https://openalex.org/W2250539671","https://openalex.org/W2342475039","https://openalex.org/W2488533857","https://openalex.org/W2510170536","https://openalex.org/W2552810951","https://openalex.org/W2584561145","https://openalex.org/W2600500166","https://openalex.org/W2610961739","https://openalex.org/W2742542661","https://openalex.org/W2749122408","https://openalex.org/W2752234108","https://openalex.org/W2767087747","https://openalex.org/W2799973650","https://openalex.org/W2801959488","https://openalex.org/W2883409523","https://openalex.org/W2886300652","https://openalex.org/W2889090126","https://openalex.org/W2894458059","https://openalex.org/W2896457183","https://openalex.org/W2963104701","https://openalex.org/W2963466847","https://openalex.org/W2963654251","https://openalex.org/W2963686995","https://openalex.org/W2963702064","https://openalex.org/W2963962398","https://openalex.org/W2963995504","https://openalex.org/W2972971501","https://openalex.org/W2995166716","https://openalex.org/W3015240477","https://openalex.org/W3015707499","https://openalex.org/W3015988193","https://openalex.org/W3016039577","https://openalex.org/W3035731479","https://openalex.org/W3094805191","https://openalex.org/W3096723250","https://openalex.org/W3096963953","https://openalex.org/W3161905931","https://openalex.org/W3162890625","https://openalex.org/W3212282286","https://openalex.org/W3215440557","https://openalex.org/W4243733441","https://openalex.org/W4297841478","https://openalex.org/W4299280181","https://openalex.org/W6730042731","https://openalex.org/W6735377749","https://openalex.org/W6735610568","https://openalex.org/W6745553787","https://openalex.org/W6748865747","https://openalex.org/W6750449527","https://openalex.org/W6763291628"],"related_works":["https://openalex.org/W4307784074","https://openalex.org/W2891616219","https://openalex.org/W2796920963","https://openalex.org/W2064483411","https://openalex.org/W2086004744","https://openalex.org/W2017516907","https://openalex.org/W2952919399","https://openalex.org/W2150149003","https://openalex.org/W3204672119","https://openalex.org/W119193395"],"abstract_inverted_index":{"Emotion":[0],"recognition":[1],"is":[2,21,47,75,117],"a":[3,36,91,114,133,141],"key":[4],"attribute":[5],"for":[6,49,137,195],"artificial":[7],"intelligence":[8],"systems":[9,97],"that":[10,94],"need":[11],"to":[12,27,68,77,119],"naturally":[13],"interact":[14],"with":[15,85,101,178,189],"humans.":[16],"However,":[17],"the":[18,28,55,65,79,104,110,121,128,150,169,172,185,190,196,202,208,213],"task":[19],"definition":[20],"still":[22],"an":[23],"open":[24],"problem":[25],"due":[26],"inherent":[29],"ambiguity":[30],"of":[31,106,168,201,216],"emotions.":[32],"In":[33],"this":[34],"paper,":[35],"novel":[37],"Bayesian":[38,186],"training":[39,187,193],"loss":[40,188,194],"based":[41],"on":[42,109,140,149,156],"per-utterance":[43,142],"Dirichlet":[44],"prior":[45],"distributions":[46],"proposed":[48,203],"verbal":[50],"emotion":[51,70,95,111,138],"recognition,":[52],"which":[53,144,211],"models":[54],"uncertainty":[56,158,180],"in":[57,166],"one-hot":[58,129],"labels":[59,102,124],"created":[60],"when":[61,175],"human":[62],"annotators":[63,107],"assign":[64],"same":[66,214],"utterance":[67],"different":[69],"classes.":[71],"An":[72],"additional":[73],"metric":[74],"used":[76,152],"evaluate":[78],"performance":[80,165],"by":[81,126,183],"detecting":[82,176],"test":[83],"utterances":[84,100,177],"high":[86,179],"labelling":[87],"uncertainty.":[88],"This":[89],"removes":[90],"major":[92],"limitation":[93],"classification":[96,139,147],"only":[98],"consider":[99],"where":[103],"majority":[105],"agree":[108],"class.":[112],"Furthermore,":[113],"frequentist":[115],"approach":[116,204],"studied":[118],"leverage":[120],"continuous-valued":[122],"\u201csoft\u201d":[123],"obtained":[125],"averaging":[127],"labels.":[130,198],"We":[131],"propose":[132],"two-branch":[134],"model":[135],"structure":[136],"basis,":[143],"achieves":[145],"state-of-the-art":[146],"results":[148],"widely":[151],"IEMOCAP":[153],"dataset.":[154],"Based":[155],"this,":[157],"estimation":[159],"experiments":[160],"were":[161],"performed.":[162],"The":[163,199],"best":[164],"terms":[167],"area":[170],"under":[171],"precision-recall":[173],"curve":[174],"was":[181,205],"achieved":[182],"interpolating":[184],"Kullback-Leibler":[191],"divergence":[192],"soft":[197],"generality":[200],"verified":[206],"using":[207],"MSP-Podcast":[209],"dataset":[210],"yielded":[212],"pattern":[215],"results.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2022-11-26T00:00:00"}