{"id":"https://openalex.org/W4408355820","doi":"https://doi.org/10.1109/icassp49660.2025.10889485","title":"Enhancing Emotion Recognition in Incomplete Data: A Novel Cross-Modal Alignment, Reconstruction, and Refinement Framework","display_name":"Enhancing Emotion Recognition in Incomplete Data: A Novel Cross-Modal Alignment, Reconstruction, and Refinement Framework","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408355820","doi":"https://doi.org/10.1109/icassp49660.2025.10889485"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10889485","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5035524175","display_name":"Haoqin Sun","orcid":"https://orcid.org/0000-0002-8554-8969"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haoqin Sun","raw_affiliation_strings":["Nankai University,TMCC, College of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Nankai University,TMCC, College of Computer Science,China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052465353","display_name":"Shiwan Zhao","orcid":"https://orcid.org/0000-0001-5068-025X"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiwan Zhao","raw_affiliation_strings":["Nankai University,TMCC, College of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Nankai University,TMCC, College of Computer Science,China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000061781","display_name":"Shaokai Li","orcid":"https://orcid.org/0000-0002-1684-043X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shaokai Li","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114949163","display_name":"Xiangyu Kong","orcid":"https://orcid.org/0000-0003-1940-8674"},"institutions":[{"id":"https://openalex.org/I23923803","display_name":"University of Exeter","ror":"https://ror.org/03yghzc09","country_code":"GB","type":"education","lineage":["https://openalex.org/I23923803"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xiangyu Kong","raw_affiliation_strings":["University of Exeter,Exeter,United Kingdom"],"affiliations":[{"raw_affiliation_string":"University of Exeter,Exeter,United Kingdom","institution_ids":["https://openalex.org/I23923803"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101483730","display_name":"Xuechen Wang","orcid":"https://orcid.org/0000-0002-3584-7821"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuechen Wang","raw_affiliation_strings":["Nankai University,TMCC, College of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Nankai University,TMCC, College of Computer Science,China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086127472","display_name":"Jiaming Zhou","orcid":"https://orcid.org/0000-0002-9298-4347"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaming Zhou","raw_affiliation_strings":["Nankai University,TMCC, College of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Nankai University,TMCC, College of Computer Science,China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113361563","display_name":"Aobo Kong","orcid":null},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aobo Kong","raw_affiliation_strings":["Nankai University,TMCC, College of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Nankai University,TMCC, College of Computer Science,China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100454388","display_name":"Yong Chen","orcid":"https://orcid.org/0000-0002-1089-0110"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yong Chen","raw_affiliation_strings":["Lingxi (Beijing) Technology Co., Ltd"],"affiliations":[{"raw_affiliation_string":"Lingxi (Beijing) Technology Co., Ltd","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073069124","display_name":"Wenjia Zeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wenjia Zeng","raw_affiliation_strings":["Lingxi (Beijing) Technology Co., Ltd"],"affiliations":[{"raw_affiliation_string":"Lingxi (Beijing) Technology Co., Ltd","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102006082","display_name":"Yong Qin","orcid":"https://orcid.org/0000-0001-9808-0456"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Qin","raw_affiliation_strings":["Nankai University,TMCC, College of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Nankai University,TMCC, College of Computer Science,China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5035524175"],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":null,"apc_paid":null,"fwci":13.7265,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.9835348,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8776999711990356,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8776999711990356,"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":0.7730000019073486,"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/modal","display_name":"Modal","score":0.7250728011131287},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.724561870098114},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.5736716389656067},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4579121470451355},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3447510302066803}],"concepts":[{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.7250728011131287},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.724561870098114},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.5736716389656067},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4579121470451355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3447510302066803},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10889485","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2146334809","https://openalex.org/W2342475039","https://openalex.org/W2481681431","https://openalex.org/W2741295496","https://openalex.org/W2809410879","https://openalex.org/W2887761937","https://openalex.org/W2936134684","https://openalex.org/W2962770129","https://openalex.org/W2962931510","https://openalex.org/W2963446712","https://openalex.org/W2965487497","https://openalex.org/W3035524453","https://openalex.org/W3175825020","https://openalex.org/W3206201541","https://openalex.org/W4214825215","https://openalex.org/W4280616225","https://openalex.org/W4296437441","https://openalex.org/W4313639237","https://openalex.org/W4372260527","https://openalex.org/W4385245566","https://openalex.org/W4385573154","https://openalex.org/W4385822516","https://openalex.org/W4385823311","https://openalex.org/W4386075815","https://openalex.org/W4390872007","https://openalex.org/W4392903039","https://openalex.org/W4392903310","https://openalex.org/W4392903647","https://openalex.org/W4396696574","https://openalex.org/W4399168695","https://openalex.org/W4402111705","https://openalex.org/W6780218876","https://openalex.org/W6789753369"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W3105646692","https://openalex.org/W4387914125"],"abstract_inverted_index":{"Multimodal":[0],"emotion":[1,54],"recognition":[2],"systems":[3],"rely":[4],"heavily":[5],"on":[6,143],"the":[7,27,109,113,119],"full":[8],"availability":[9],"of":[10,112,122,129,136],"modalities,":[11,131],"suffering":[12],"significant":[13],"performance":[14,121],"declines":[15],"when":[16],"modal":[17,66],"data":[18],"is":[19],"incomplete.":[20],"To":[21],"tackle":[22],"this":[23],"issue,":[24],"we":[25],"present":[26],"Cross-Modal":[28],"Alignment,":[29],"Reconstruction,":[30],"and":[31,45,52,70,87,103,139,145],"Refinement":[32],"(CM-ARR)":[33],"framework,":[34],"an":[35],"innovative":[36],"approach":[37],"that":[38],"sequentially":[39],"engages":[40],"in":[41],"cross-modal":[42],"alignment,":[43],"reconstruction,":[44],"refinement":[46,92],"phases":[47],"to":[48,63,82,99],"handle":[49],"missing":[50,89,130],"modalities":[51],"enhance":[53],"recognition.":[55],"This":[56],"framework":[57],"utilizes":[58],"unsupervised":[59],"distribution-based":[60],"contrastive":[61,97],"learning":[62,98],"align":[64],"heterogeneous":[65],"distributions,":[67],"reducing":[68],"discrepancies":[69],"modeling":[71],"semantic":[72,101],"uncertainty":[73],"effectively.":[74],"The":[75,91],"reconstruction":[76],"phase":[77,93],"applies":[78],"normalizing":[79],"flow":[80],"models":[81],"transform":[83],"these":[84],"aligned":[85],"distributions":[86],"recover":[88],"modalities.":[90],"employs":[94],"supervised":[95],"point-based":[96],"disrupt":[100],"correlations":[102],"accentuate":[104],"emotional":[105],"traits,":[106],"thereby":[107],"enriching":[108],"affective":[110],"content":[111],"reconstructed":[114],"representations.":[115],"Extensive":[116],"experiments":[117],"confirm":[118],"superior":[120],"CM-ARR.":[123],"Notably,":[124],"averaged":[125],"across":[126],"six":[127],"scenarios":[128],"CM-ARR":[132],"achieves":[133],"absolute":[134],"improvements":[135],"2.11%/2.12%":[137],"(WAR/UAR),":[138,141],"1.71%/1.96%":[140],"respectively,":[142],"IEMOCAP":[144],"MSP-IMPROV":[146],"datasets.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}