{"id":"https://openalex.org/W7117239698","doi":"https://doi.org/10.1145/3786588","title":"MSDA-Net: Multi-source Domain Adaptive Network for Multi-modal Emotion Recognition","display_name":"MSDA-Net: Multi-source Domain Adaptive Network for Multi-modal Emotion Recognition","publication_year":2025,"publication_date":"2025-12-25","ids":{"openalex":"https://openalex.org/W7117239698","doi":"https://doi.org/10.1145/3786588"},"language":"en","primary_location":{"id":"doi:10.1145/3786588","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3786588","pdf_url":null,"source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","raw_type":"journal-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/A5020214488","display_name":"Cheng Cheng","orcid":"https://orcid.org/0000-0002-2138-6286"},"institutions":[{"id":"https://openalex.org/I153374732","display_name":"Liaoning Normal University","ror":"https://ror.org/04c3cgg32","country_code":"CN","type":"education","lineage":["https://openalex.org/I153374732"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Cheng Cheng","raw_affiliation_strings":["Liaoning Normal University"],"affiliations":[{"raw_affiliation_string":"Liaoning Normal University","institution_ids":["https://openalex.org/I153374732"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042100325","display_name":"Xingxing Cai","orcid":"https://orcid.org/0000-0003-3673-9248"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingxing Cai","raw_affiliation_strings":["School of Information Engineering, Huzhou University"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Huzhou University","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121245403","display_name":"Hengrui Qi","orcid":null},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hengrui Qi","raw_affiliation_strings":["The University of British Columbia"],"affiliations":[{"raw_affiliation_string":"The University of British Columbia","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121255454","display_name":"Wenyun Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenyun Chen","raw_affiliation_strings":["School of Information Engineering, Huzhou University"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Huzhou University","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051458485","display_name":"Y. Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Zhang","raw_affiliation_strings":["School of Information Engineering, Huzhou University"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Huzhou University","institution_ids":["https://openalex.org/I3018263800"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5020214488"],"corresponding_institution_ids":["https://openalex.org/I153374732"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.71666541,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":"1","first_page":"1","last_page":"22"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.986299991607666,"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":0.986299991607666,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.007899999618530273,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.0003000000142492354,"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/feature","display_name":"Feature (linguistics)","score":0.6636000275611877},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5203999876976013},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.5180000066757202},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4966999888420105},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.46709999442100525},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.45419999957084656},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.3968999981880188}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7210000157356262},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6636000275611877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5864999890327454},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5203999876976013},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.5180000066757202},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4966999888420105},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.46709999442100525},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.45419999957084656},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4074000120162964},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.3968999981880188},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.36160001158714294},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.3540000021457672},{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.35339999198913574},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3066999912261963},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.29159998893737793},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2558000087738037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3786588","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3786588","pdf_url":null,"source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1947251450","https://openalex.org/W2165698076","https://openalex.org/W2171931442","https://openalex.org/W2625929003","https://openalex.org/W2786768213","https://openalex.org/W2787581402","https://openalex.org/W2790404832","https://openalex.org/W2911220936","https://openalex.org/W2926366943","https://openalex.org/W2945600262","https://openalex.org/W2964051877","https://openalex.org/W2964288524","https://openalex.org/W2968176343","https://openalex.org/W3005283300","https://openalex.org/W3021632667","https://openalex.org/W3027131706","https://openalex.org/W3080946082","https://openalex.org/W3089557188","https://openalex.org/W3090425814","https://openalex.org/W3126607918","https://openalex.org/W3157818078","https://openalex.org/W3163658025","https://openalex.org/W3165847061","https://openalex.org/W4200006449","https://openalex.org/W4206654584","https://openalex.org/W4223909097","https://openalex.org/W4226182667","https://openalex.org/W4226287122","https://openalex.org/W4283384314","https://openalex.org/W4285109316","https://openalex.org/W4287887175","https://openalex.org/W4289816897","https://openalex.org/W4291910522","https://openalex.org/W4313525550","https://openalex.org/W4313527457","https://openalex.org/W4316660747","https://openalex.org/W4376607505","https://openalex.org/W4379233567","https://openalex.org/W4381785707","https://openalex.org/W4387951221","https://openalex.org/W4387969127","https://openalex.org/W4390992285","https://openalex.org/W4394828357","https://openalex.org/W4400111405","https://openalex.org/W4400314496","https://openalex.org/W4411358937"],"related_works":[],"abstract_inverted_index":{"Electroencephalogram":[0],"(EEG)":[1],"has":[2],"shown":[3],"g":[4],"reat":[5],"potential":[6],"in":[7,179],"multi-modal":[8],"emotion":[9],"recognition":[10,83],"(MER)":[11],"due":[12],"to":[13,16,28,50,74,93,117,128,137],"its":[14,177],"ability":[15],"directly":[17],"capture":[18,118,138],"emotional":[19,120],"states.":[20],"However,":[21],"the":[22,130,166,172],"nonstationarity":[23],"of":[24,174],"EEG":[25],"signals":[26,53],"leads":[27],"significant":[29,45],"variations":[30],"across":[31],"subjects":[32],"and":[33,77,81,103,141,152,168],"sessions,":[34],"posing":[35],"challenges":[36],"for":[37,71],"subject-independent":[38],"MER.":[39],"While":[40],"previous":[41],"methods":[42],"have":[43],"made":[44],"progress,":[46],"they":[47],"often":[48],"fail":[49],"integrate":[51,94],"multimodal":[52],"into":[54,158],"transfer":[55],"learning":[56],"frameworks":[57],"effectively.":[58],"To":[59,108],"address":[60],"this":[61],"limitation,":[62],"we":[63,86,112,123,146],"propose":[64],"a":[65,89,159],"Multi-source":[66],"Domain":[67],"Adaptive":[68],"Network":[69],"(MSDA-Net)":[70],"MER,":[72],"designed":[73],"mitigate":[75],"cross-subject":[76],"cross-session":[78],"distribution":[79],"shifts":[80],"enhance":[82],"performance.":[84,182],"Specifically,":[85],"first":[87],"design":[88],"feature":[90,101,115,131],"alignment":[91],"module":[92,127],"features":[95],"from":[96],"different":[97,134],"modalities,":[98,135],"generating":[99],"cross-modal":[100,142],"representations":[102,132],"extracting":[104],"representative":[105],"shared":[106],"features.":[107],"further":[109],"improve":[110],"generalization,":[111],"incorporate":[113],"domain-specific":[114],"extractors":[116],"domain-invariant":[119],"representations.":[121],"Additionally,":[122],"introduce":[124],"an":[125],"adapter":[126],"adjust":[129],"between":[133],"aiming":[136],"inter-individual":[139],"differences":[140],"correlations":[143],"better.":[144],"Finally,":[145],"unify":[147],"classification":[148],"loss,":[149,151],"discrepancy":[150,155],"maximum":[153],"mean":[154],"(MMD)":[156],"loss":[157],"joint":[160],"optimization":[161],"framework.":[162],"Abundant":[163],"experiments":[164],"on":[165],"SEED":[167],"SEED-IV":[169],"datasets":[170],"demonstrate":[171],"superiority":[173],"MSDA-Net,":[175],"highlighting":[176],"effectiveness":[178],"improving":[180],"MER":[181]},"counts_by_year":[],"updated_date":"2026-01-14T00:41:55.809242","created_date":"2025-12-25T00:00:00"}
