{"id":"https://openalex.org/W7224087694","doi":"https://doi.org/10.5281/zenodo.23729862","title":"Evaluation of Multimodal Face and Voice Classification of Emotion-Derived Negative-Affect Labels","display_name":"Evaluation of Multimodal Face and Voice Classification of Emotion-Derived Negative-Affect Labels","publication_year":2026,"publication_date":"2026-10-28","ids":{"openalex":"https://openalex.org/W7224087694","doi":"https://doi.org/10.5281/zenodo.23729862"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.23729862","doi":"https://doi.org/10.5281/zenodo.23729862","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23729862","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"volume":null,"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.23729862","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119743218","display_name":"Chandra Prakash Singar","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chandra Prakash Singar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160003070","display_name":"Puja Gupta","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Puja Gupta","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136574516","display_name":"Meet Lahori","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meet Lahori","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022920206","display_name":"Krishna Saxena","orcid":"https://orcid.org/0000-0002-2237-5378","observed_orcids":["https://orcid.org/0000-0002-2237-5378"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Krishna Saxena","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136507485","display_name":"Shaivi Barwe","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shaivi Barwe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5160054978","display_name":"Neha Agrawal","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Neha Agrawal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":0.88033203,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":1.0,"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":1.0,"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":0.0,"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/T11448","display_name":"Face recognition and analysis","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/negative-affect","display_name":"negative affect","score":0.7239999771118164},{"id":"https://openalex.org/keywords/facial-expressions","display_name":"facial expressions","score":0.7139999866485596},{"id":"https://openalex.org/keywords/speech-emotion-recognition","display_name":"speech emotion recognition","score":0.6949999928474426},{"id":"https://openalex.org/keywords/decision-level-fusion","display_name":"decision fusion","score":0.8870000243186951},{"id":"https://openalex.org/keywords/anger","display_name":"anger","score":0.4519999921321869},{"id":"https://openalex.org/keywords/disgust","display_name":"disgust","score":0.9869999885559082},{"id":"https://openalex.org/keywords/fear","display_name":"fear","score":0.9959999918937683},{"id":"https://openalex.org/keywords/happiness","display_name":"happiness","score":0.47099998593330383},{"id":"https://openalex.org/keywords/neutrals","display_name":"neutrals","score":0.625},{"id":"https://openalex.org/keywords/calm","display_name":"CALM","score":0.9800000190734863},{"id":"https://openalex.org/keywords/crema-d","display_name":"CREMA-D","score":0.8519999980926514},{"id":"https://openalex.org/keywords/ravdess","display_name":"RAVDESS","score":1.0},{"id":"https://openalex.org/keywords/mel-frequency-cepstral-coefficients","display_name":"Mel-frequency cepstral coefficients","score":0.9129999876022339},{"id":"https://openalex.org/keywords/stress-detection","display_name":"stress detection","score":0.38600000739097595}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.70660001039505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.652999997138977},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6349999904632568},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.5685999989509583},{"id":"https://openalex.org/C2778739407","wikidata":"https://www.wikidata.org/wiki/Q165372","display_name":"CLIPS","level":2,"score":0.5647000074386597},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5638999938964844},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5634999871253967},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5084999799728394},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.503000020980835},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.40860000252723694},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.38269999623298645},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.3815999925136566},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.36910000443458557},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.353300005197525},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3206999897956848},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.28049999475479126},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.27630001306533813}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5281/zenodo.23729862","doi":"https://doi.org/10.5281/zenodo.23729862","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23729862","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},{"id":"doi:10.5281/zenodo.23729863","doi":"https://doi.org/10.5281/zenodo.23729863","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23729863","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.5281/zenodo.23729862","doi":"https://doi.org/10.5281/zenodo.23729862","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23729862","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2899953283","https://openalex.org/W7220083576","https://openalex.org/W7214758464","https://openalex.org/W2133924623","https://openalex.org/W7002242839","https://openalex.org/W74190392","https://openalex.org/W1995794789","https://openalex.org/W2286935440","https://openalex.org/W1997541854","https://openalex.org/W4306746108"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"an":[3],"end-to-end":[4],"prototype":[5],"that":[6,73],"classifies":[7],"emotion-derived":[8],"negative-affect":[9],"labels":[10],"from":[11,18,91,194],"facial":[12,76],"video":[13],"and":[14,23,27,35,41,44,67,84,94,103,134,145,171,177,205],"speech":[15],"audio.":[16],"Clips":[17],"two":[19,195],"acted-emotion":[20],"corpora,":[21],"CREMA-D":[22,162],"RAVDESS,":[24],"are":[25,38,47,100,113,201],"combined":[26],"mapped":[28],"to":[29],"a":[30,65,81,85,118],"binary":[31],"target:":[32],"angry,":[33],"disgust,":[34],"fearful":[36],"clips":[37,46],"labeled":[39,48],"1,":[40],"happy,":[42],"neutral,":[43],"calm":[45],"0.":[49],"Because":[50],"both":[51],"corpora":[52],"annotate":[53],"acted":[54],"expression":[55],"rather":[56],"than":[57],"physiological":[58],"or":[59],"self-reported":[60],"stress,":[61],"the":[62,68,142,148,155,161,168,172,185,206],"target":[63],"is":[64,158,179,210],"proxy,":[66],"results":[69],"describe":[70],"classification":[71],"of":[72,122],"proxy.":[74],"A":[75],"branch":[77,87,144,157],"(ResNet18":[78],"embeddings":[79],"with":[80,97,138],"multilayer":[82],"perceptron)":[83],"voice":[86,149],"(240":[88],"statistics":[89],"derived":[90],"40":[92],"MFCCs":[93],"their":[95],"deltas,":[96],"logistic":[98],"regression)":[99],"evaluated":[101,212],"separately":[102],"under":[104],"weighted":[105],"late":[106,125],"fusion":[107,126,152,176],"(0.40":[108],"face,":[109],"0.60":[110],"voice).":[111],"Splits":[112],"grouped":[114],"by":[115,184],"actor.":[116],"On":[117],"held-out":[119],"test":[120,163],"set":[121],"743":[123],"clips,":[124],"achieved":[127],"78.33%":[128],"accuracy,":[129],"82.85%":[130],"F1-score,":[131],"86.44%":[132],"recall,":[133],"0.8522":[135],"ROC-AUC,":[136],"compared":[137],"76.04%":[139],"accuracy":[140,173],"for":[141,147],"face":[143,156],"67.29%":[146],"branch.":[150],"The":[151,189],"gain":[153],"over":[154],"clear":[159],"on":[160,167],"subset":[164],"but":[165],"reverses":[166],"RAVDESS":[169],"subset,":[170],"difference":[174],"between":[175],"face-only":[178],"not":[180,202,211],"established":[181],"as":[182],"significant":[183],"analyses":[186],"reported":[187],"here.":[188],"system":[190],"also":[191],"displays":[192],"outputs":[193,200],"pretrained":[196],"visible-expression":[197],"models.":[198],"These":[199],"stress":[203],"evidence,":[204],"application\u2019s":[207],"expression-priority":[208],"rule":[209],"in":[213],"this":[214],"paper.":[215]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-10-29T00:00:00"}