{"id":"https://openalex.org/W4392903917","doi":"https://doi.org/10.1109/icassp48485.2024.10446499","title":"Multi-Source Unsupervised Transfer Components Learning for Cross-Domain Speech Emotion Recognition","display_name":"Multi-Source Unsupervised Transfer Components Learning for Cross-Domain Speech Emotion Recognition","publication_year":2024,"publication_date":"2024-03-18","ids":{"openalex":"https://openalex.org/W4392903917","doi":"https://doi.org/10.1109/icassp48485.2024.10446499"},"language":"en","primary_location":{"id":"doi:10.1109/icassp48485.2024.10446499","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10446499","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 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/A5101380343","display_name":"Shenjie Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shenjie Jiang","raw_affiliation_strings":["Yantai University,School of Computer and Control Engineering,Yantai,China,264005"],"affiliations":[{"raw_affiliation_string":"Yantai University,School of Computer and Control Engineering,Yantai,China,264005","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009279384","display_name":"Peng Song","orcid":"https://orcid.org/0000-0002-6567-663X"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Song","raw_affiliation_strings":["Yantai University,School of Computer and Control Engineering,Yantai,China,264005"],"affiliations":[{"raw_affiliation_string":"Yantai University,School of Computer and Control Engineering,Yantai,China,264005","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000061781","display_name":"Shaokai Li","orcid":"https://orcid.org/0000-0002-1684-043X"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaokai Li","raw_affiliation_strings":["Yantai University,School of Computer and Control Engineering,Yantai,China,264005"],"affiliations":[{"raw_affiliation_string":"Yantai University,School of Computer and Control Engineering,Yantai,China,264005","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108046985","display_name":"Run Wang","orcid":"https://orcid.org/0009-0007-7376-8378"},"institutions":[{"id":"https://openalex.org/I18452120","display_name":"Yantai University","ror":"https://ror.org/01rp41m56","country_code":"CN","type":"education","lineage":["https://openalex.org/I18452120"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Run Wang","raw_affiliation_strings":["Yantai University,School of Computer and Control Engineering,Yantai,China,264005"],"affiliations":[{"raw_affiliation_string":"Yantai University,School of Computer and Control Engineering,Yantai,China,264005","institution_ids":["https://openalex.org/I18452120"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029771864","display_name":"Wenming Zheng","orcid":"https://orcid.org/0000-0002-7764-5179"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenming Zheng","raw_affiliation_strings":["Key Laboratory of Child Development and Learning Science (Southeast University) Ministry of Education, Southeast University,Nanjing,China,210096"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Child Development and Learning Science (Southeast University) Ministry of Education, Southeast University,Nanjing,China,210096","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101380343"],"corresponding_institution_ids":["https://openalex.org/I18452120"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02901965,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"10226","last_page":"10230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9990000128746033,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9979000091552734,"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/T11309","display_name":"Music and Audio Processing","score":0.9944999814033508,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7927824258804321},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.7355446219444275},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7298120856285095},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6814717650413513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.585476815700531},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5205743908882141},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4987201690673828},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4769552946090698},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4761923849582672},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4645760953426361},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3475397229194641},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0838029682636261}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7927824258804321},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.7355446219444275},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7298120856285095},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6814717650413513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.585476815700531},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5205743908882141},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4987201690673828},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4769552946090698},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4761923849582672},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4645760953426361},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3475397229194641},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0838029682636261},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/icassp48485.2024.10446499","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp48485.2024.10446499","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W147964346","https://openalex.org/W175750906","https://openalex.org/W589698015","https://openalex.org/W1581984155","https://openalex.org/W2090042335","https://openalex.org/W2096943734","https://openalex.org/W2113087918","https://openalex.org/W2142398106","https://openalex.org/W2146334809","https://openalex.org/W2194775991","https://openalex.org/W2404205548","https://openalex.org/W2783924111","https://openalex.org/W2935033494","https://openalex.org/W2963693396","https://openalex.org/W2968584961","https://openalex.org/W2997399314","https://openalex.org/W3041133507","https://openalex.org/W3109943296","https://openalex.org/W3113497772","https://openalex.org/W3119997721","https://openalex.org/W3135939397","https://openalex.org/W3167120905","https://openalex.org/W4210702020","https://openalex.org/W4288054906","https://openalex.org/W4302009885","https://openalex.org/W4372189490","https://openalex.org/W4381786099","https://openalex.org/W4385823356"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W1975632186","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175"],"abstract_inverted_index":{"As":[0],"an":[1,107],"important":[2],"research":[3],"direction":[4],"in":[5],"the":[6,115,129],"field":[7],"of":[8,117],"speech":[9,13],"signal":[10],"processing,":[11],"cross-domain":[12,56,95],"emotion":[14],"recognition":[15],"(SER)":[16],"has":[17],"attracted":[18],"extensive":[19],"attention.":[20],"In":[21,58],"practice,":[22],"it":[23,68],"is":[24,91,111],"challenging":[25],"to":[26,35,69,73,93,97,113],"collect":[27],"enough":[28],"labeled":[29],"samples":[30,96],"from":[31],"single":[32],"source":[33,119],"domain":[34],"train":[36],"robust":[37],"classifiers.":[38],"To":[39],"this":[40,42],"end,":[41],"paper":[43],"presents":[44],"a":[45,63,87],"novel":[46],"method":[47],"named":[48],"multi-source":[49,70],"unsupervised":[50],"transfer":[51,104],"components":[52,82],"learning":[53],"(MUTCL)":[54],"for":[55],"SER.":[57],"MUTCL,":[59],"we":[60],"first":[61],"adopt":[62],"PCA-like":[64],"strategy":[65,90,110],"and":[66,78,128],"apply":[67],"domains,":[71],"aiming":[72],"preserve":[74],"both":[75],"intra-domain":[76],"individuality":[77],"inter-domain":[79],"commonality":[80],"principal":[81],"within":[83],"each":[84,118],"domain.":[85,120],"Simultaneously,":[86],"simple":[88],"alignment":[89],"developed":[92],"guide":[94],"have":[98],"similar":[99],"structures,":[100],"thus":[101],"preserving":[102],"more":[103],"components.":[105],"Moreover,":[106],"adaptive":[108],"weight":[109],"utilized":[112],"determine":[114],"contribution":[116],"We":[121],"conduct":[122],"experiments":[123],"on":[124],"five":[125],"benchmark":[126],"datasets,":[127],"results":[130],"show":[131],"that":[132],"MUTCL":[133],"achieves":[134],"excellent":[135],"performance":[136],"compared":[137],"with":[138],"some":[139],"state-of-the-art":[140],"methods.":[141]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}