{"id":"https://openalex.org/W4415537951","doi":"https://doi.org/10.1145/3746027.3762018","title":"Listening to the Unspoken: Exploring '365' Aspects of Multimodal Interview Performance Assessment","display_name":"Listening to the Unspoken: Exploring '365' Aspects of Multimodal Interview Performance Assessment","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415537951","doi":"https://doi.org/10.1145/3746027.3762018"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3762018","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3762018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","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/A5019391894","display_name":"Jia Li","orcid":"https://orcid.org/0000-0001-9446-249X"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jia Li","raw_affiliation_strings":["Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yang Wang","orcid":"https://orcid.org/0000-0001-7243-2177"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Wang","raw_affiliation_strings":["Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038593588","display_name":"Wenhao Qian","orcid":"https://orcid.org/0009-0006-2574-4630"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhao Qian","raw_affiliation_strings":["Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108680971","display_name":"Jialong Hu","orcid":"https://orcid.org/0009-0008-3196-2188"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jialong Hu","raw_affiliation_strings":["Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040235604","display_name":"Zhenzhen Hu","orcid":"https://orcid.org/0000-0003-1042-8361"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]},{"id":"https://openalex.org/I39774598","display_name":"Hefei University","ror":"https://ror.org/01f5rdf64","country_code":"CN","type":"education","lineage":["https://openalex.org/I39774598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenzhen Hu","raw_affiliation_strings":["Hefei University of Technology of Anhui Province, Hefei, China and Intelligent Interconnected Systems Laboratory of Anhui Province, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology of Anhui Province, Hefei, China and Intelligent Interconnected Systems Laboratory of Anhui Province, Hefei, China","institution_ids":["https://openalex.org/I39774598","https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051332325","display_name":"Richang Hong","orcid":"https://orcid.org/0000-0001-5461-3986"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Richang Hong","raw_affiliation_strings":["Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100377147","display_name":"Meng Wang","orcid":"https://orcid.org/0000-0002-3094-7735"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Wang","raw_affiliation_strings":["Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5019391894"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34522794,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"13909","last_page":"13916"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12593","display_name":"Communication in Education and Healthcare","score":0.9771999716758728,"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"}},"topics":[{"id":"https://openalex.org/T12593","display_name":"Communication in Education and Healthcare","score":0.9771999716758728,"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"}},{"id":"https://openalex.org/T10366","display_name":"Discourse Analysis in Language Studies","score":0.9455000162124634,"subfield":{"id":"https://openalex.org/subfields/1208","display_name":"Literature and Literary Theory"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/active-listening","display_name":"Active listening","score":0.7159000039100647},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.6632999777793884},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6128000020980835},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5842999815940857},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4787999987602234},{"id":"https://openalex.org/keywords/multimodal-learning","display_name":"Multimodal learning","score":0.3301999866962433}],"concepts":[{"id":"https://openalex.org/C177291462","wikidata":"https://www.wikidata.org/wiki/Q423038","display_name":"Active listening","level":2,"score":0.7159000039100647},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.6632999777793884},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6220999956130981},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6128000020980835},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5842999815940857},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4787999987602234},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40560001134872437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3971000015735626},{"id":"https://openalex.org/C2780660688","wikidata":"https://www.wikidata.org/wiki/Q25052564","display_name":"Multimodal learning","level":2,"score":0.3301999866962433},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26739999651908875},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.26420000195503235},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2547999918460846},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3762018","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3762018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G178441916","display_name":null,"funder_award_id":"JZ2024HGTG031,JZ2025HGTB0226,PA2025IISL0110","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4343481052","display_name":null,"funder_award_id":"62172138,62202139","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2020649925","https://openalex.org/W2037248153","https://openalex.org/W2085662862","https://openalex.org/W2112796928","https://openalex.org/W2970602317","https://openalex.org/W2997573100","https://openalex.org/W4224140271","https://openalex.org/W4296079469","https://openalex.org/W4311770445","https://openalex.org/W4387041709","https://openalex.org/W4389060417","https://openalex.org/W4390479873","https://openalex.org/W4390738777","https://openalex.org/W4391482516","https://openalex.org/W4392578770","https://openalex.org/W4392607660","https://openalex.org/W4402715273","https://openalex.org/W4404590772","https://openalex.org/W4404823082","https://openalex.org/W4405131137","https://openalex.org/W4406526006"],"related_works":[],"abstract_inverted_index":{"Interview":[0],"performance":[1,31,172],"assessment":[2],"is":[3,177],"essential":[4],"for":[5,9,100,118],"determining":[6],"candidates'":[7],"suitability":[8],"professional":[10],"positions.":[11],"To":[12,83],"ensure":[13],"holistic":[14],"and":[15,22,38,44,60,103,133,141,164,169],"fair":[16],"evaluations,":[17],"we":[18,87],"propose":[19],"a":[20,64,75,89,111,145],"novel":[21],"comprehensive":[23,140],"framework":[24,50,152],"that":[25],"explores":[26],"''365''":[27],"aspects":[28],"of":[29,149],"interview":[30,171],"by":[32],"integrating":[33],"three":[34],"modalities":[35],"(video,":[36],"audio,":[37],"text),":[39],"six":[40],"responses":[41,109],"per":[42],"candidate,":[43],"five":[45,120],"key":[46],"evaluation":[47],"dimensions.":[48,122],"The":[49,174],"employs":[51],"modality-specific":[52],"feature":[53,81],"extractors":[54],"to":[55,114,125],"encode":[56],"heterogeneous":[57],"data":[58],"streams":[59],"subsequently":[61],"fused":[62],"via":[63],"Shared":[65],"Compression":[66],"Multilayer":[67],"Perceptron.":[68],"This":[69],"module":[70],"compresses":[71],"multimodal":[72,137,170],"embeddings":[73],"into":[74],"unified":[76],"latent":[77],"space,":[78],"facilitating":[79],"efficient":[80],"interaction.":[82],"enhance":[84],"prediction":[85],"robustness,":[86],"incorporate":[88],"two-level":[90],"ensemble":[91],"learning":[92],"strategy:":[93],"(1)":[94],"independent":[95],"regression":[96],"heads":[97],"predict":[98],"scores":[99,117],"each":[101],"response,":[102],"(2)":[104],"predictions":[105],"are":[106],"aggregated":[107],"across":[108],"using":[110],"mean-pooling":[112],"mechanism":[113],"produce":[115],"final":[116],"the":[119,126,157],"target":[121],"By":[123],"listening":[124],"unspoken,":[127],"our":[128,151],"approach":[129],"captures":[130],"both":[131],"explicit":[132],"implicit":[134],"cues":[135],"from":[136],"data,":[138],"enabling":[139],"unbiased":[142],"assessments.":[143],"Achieving":[144],"multi-dimensional":[146],"average":[147],"MSE":[148],"0.1824,":[150],"secured":[153],"first":[154],"place":[155],"in":[156,166],"AVI":[158],"Challenge":[159],"2025,":[160],"demonstrating":[161],"its":[162],"effectiveness":[163],"robustness":[165],"advancing":[167],"automated":[168],"assessment.":[173],"full":[175],"implementation":[176],"available":[178],"at":[179],"https://github.com/Qianvenh/AVI2025-Track2.":[180]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-25T00:00:00"}