{"id":"https://openalex.org/W4289134328","doi":"https://doi.org/10.3390/e24081046","title":"Progressively Discriminative Transfer Network for Cross-Corpus Speech Emotion Recognition","display_name":"Progressively Discriminative Transfer Network for Cross-Corpus Speech Emotion Recognition","publication_year":2022,"publication_date":"2022-07-29","ids":{"openalex":"https://openalex.org/W4289134328","doi":"https://doi.org/10.3390/e24081046","pmid":"https://pubmed.ncbi.nlm.nih.gov/36010710"},"language":"en","primary_location":{"id":"doi:10.3390/e24081046","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24081046","pdf_url":"https://www.mdpi.com/1099-4300/24/8/1046/pdf?version=1661236020","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/24/8/1046/pdf?version=1661236020","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054796879","display_name":"Cheng Lu","orcid":"https://orcid.org/0000-0002-1477-1020"},"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":"Cheng Lu","raw_affiliation_strings":["Key Laboratory of Child Development and Learning Science (Ministry of Education), Southeast University, Nanjing 210096, China","School of Information Science and Engineering, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Child Development and Learning Science (Ministry of Education), Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Information Science and Engineering, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038686056","display_name":"Chuangao Tang","orcid":"https://orcid.org/0000-0002-3653-136X"},"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":"Chuangao Tang","raw_affiliation_strings":["Key Laboratory of Child Development and Learning Science (Ministry of Education), Southeast University, Nanjing 210096, China","School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Child Development and Learning Science (Ministry of Education), Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100720459","display_name":"Jiacheng Zhang","orcid":"https://orcid.org/0009-0008-5991-3732"},"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":"Jiacheng Zhang","raw_affiliation_strings":["Key Laboratory of Child Development and Learning Science (Ministry of Education), Southeast University, Nanjing 210096, China","School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Child Development and Learning Science (Ministry of Education), Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027316177","display_name":"Yuan Zong","orcid":"https://orcid.org/0000-0002-0839-8792"},"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":true,"raw_author_name":"Yuan Zong","raw_affiliation_strings":["Key Laboratory of Child Development and Learning Science (Ministry of Education), Southeast University, Nanjing 210096, China","School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Child Development and Learning Science (Ministry of Education), Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5027316177"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":2.0122,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.86334251,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"24","issue":"8","first_page":"1046","last_page":"1046"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9947999715805054,"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/T10860","display_name":"Speech and Audio Processing","score":0.9836999773979187,"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/discriminative-model","display_name":"Discriminative model","score":0.8132055401802063},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7553683519363403},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6553547382354736},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6061410307884216},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5343351364135742},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5138940811157227},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5021655559539795},{"id":"https://openalex.org/keywords/valence","display_name":"Valence (chemistry)","score":0.486873060464859},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4384860396385193},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.4260634183883667},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3985602855682373}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8132055401802063},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7553683519363403},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6553547382354736},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6061410307884216},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5343351364135742},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5138940811157227},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5021655559539795},{"id":"https://openalex.org/C168900304","wikidata":"https://www.wikidata.org/wiki/Q171407","display_name":"Valence (chemistry)","level":2,"score":0.486873060464859},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4384860396385193},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.4260634183883667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3985602855682373},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e24081046","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24081046","pdf_url":"https://www.mdpi.com/1099-4300/24/8/1046/pdf?version=1661236020","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:36010710","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36010710","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:a4b93a34801643199dcba9a9d0474468","is_oa":true,"landing_page_url":"https://doaj.org/article/a4b93a34801643199dcba9a9d0474468","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 24, Iss 8, p 1046 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/24/8/1046/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e24081046","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 24; Issue 8; Pages: 1046","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9407047","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9407047","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e24081046","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24081046","pdf_url":"https://www.mdpi.com/1099-4300/24/8/1046/pdf?version=1661236020","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4289134328.pdf"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W175750906","https://openalex.org/W1600088287","https://openalex.org/W1731081199","https://openalex.org/W2032254851","https://openalex.org/W2066064791","https://openalex.org/W2113087918","https://openalex.org/W2125462608","https://openalex.org/W2149628368","https://openalex.org/W2149933564","https://openalex.org/W2163605009","https://openalex.org/W2165698076","https://openalex.org/W2168692779","https://openalex.org/W2187089797","https://openalex.org/W2322208196","https://openalex.org/W2503045345","https://openalex.org/W2614874155","https://openalex.org/W2735297260","https://openalex.org/W2766272105","https://openalex.org/W2790404832","https://openalex.org/W2794365923","https://openalex.org/W2895006884","https://openalex.org/W2924116307","https://openalex.org/W2963447013","https://openalex.org/W2964288524","https://openalex.org/W2980393359","https://openalex.org/W2982195474","https://openalex.org/W2983165789","https://openalex.org/W3021632667","https://openalex.org/W3098571047","https://openalex.org/W3161933272","https://openalex.org/W3208366642","https://openalex.org/W4286544676","https://openalex.org/W6637618735","https://openalex.org/W6682889407","https://openalex.org/W6713955831"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2967180365"],"abstract_inverted_index":{"Cross-corpus":[0],"speech":[1,106,151,191,201,231,297],"emotion":[2,103,118,123,147,177,192,202,235,294],"recognition":[3],"(SER)":[4],"is":[5,110,244],"a":[6,88,131,211,238],"challenging":[7],"task,":[8],"and":[9,25,58,61,160,181,198,216,258,276,288,312],"its":[10],"difficulty":[11],"lies":[12],"in":[13,67,87,140,170],"the":[14,17,21,32,36,52,56,64,78,83,97,102,114,117,146,155,158,171,223,227,250,256,263,282,286,293,320],"mismatch":[15,156,284],"between":[16,55,157,255,285],"feature":[18,90,172,194,253],"distributions":[19,84,254],"of":[20,105,116,150,174,190,230,252,265,296,302],"training":[22],"(source":[23],"domain)":[24,28],"testing":[26],"(target":[27],"data,":[29],"leading":[30],"to":[31,50,112,225,246],"performance":[33,66],"degradation":[34],"when":[35],"model":[37],"deals":[38],"with":[39],"new":[40],"domain":[41,47,53,98,283],"data.":[42],"Previous":[43],"works":[44],"explore":[45],"utilizing":[46],"adaptation":[48],"(DA)":[49],"eliminate":[51,249,281],"shift":[54],"source":[57,159,257,287],"target":[59,161,259,289],"domains":[60,86],"have":[62,204],"achieved":[63],"promising":[65],"SER.":[68],"However,":[69],"these":[70],"methods":[71],"mainly":[72],"treat":[73],"cross-corpus":[74,138,304],"tasks":[75,305],"simply":[76],"as":[77,222],"DA":[79],"problem,":[80],"directly":[81],"aligning":[82],"across":[85],"common":[89],"space.":[91],"In":[92,163],"this":[93,127,141],"case,":[94],"excessively":[95],"narrowing":[96],"distance":[99],"will":[100],"impair":[101],"discrimination":[104,148,295],"features":[107,152,203],"since":[108],"it":[109],"difficult":[111],"maintain":[113],"completeness":[115],"space":[119],"only":[120],"by":[121,267],"an":[122,217,234],"classifier.":[124,236],"To":[125],"overcome":[126],"issue,":[128],"we":[129,165,209,278],"propose":[130],"progressively":[132],"discriminative":[133,228],"transfer":[134],"network":[135],"(PDTN)":[136],"for":[137],"SER":[139],"paper,":[142],"which":[143],"can":[144,279],"enhance":[145],"ability":[149],"while":[153,291],"eliminating":[154],"corpora.":[162],"detail,":[164],"design":[166],"two":[167],"special":[168],"losses":[169],"layers":[173],"PDTN,":[175],"i.e.,":[176,271,309],"discriminant":[178],"loss":[179,184,214,220,242,273],"Ld":[180,224],"distribution":[182,240],"alignment":[183,241],"La.":[185],"By":[186],"incorporating":[187],"prior":[188],"knowledge":[189],"into":[193],"learning":[195,229],"(i.e.,":[196],"high":[197],"low":[199],"valence":[200],"their":[205],"respective":[206],"cluster":[207],"centers),":[208],"integrate":[210],"valence-aware":[212],"center":[213,219],"Lv":[215],"emotion-aware":[218],"Lc":[221],"guarantee":[226],"emotions":[232],"except":[233],"Furthermore,":[237],"multi-layer":[239],"La":[243],"adopted":[245],"more":[247],"precisely":[248],"discrepancy":[251],"domains.":[260],"Finally,":[261],"through":[262],"optimization":[264],"PDTN":[266,318],"combining":[268],"three":[269,307],"losses,":[270],"cross-entropy":[272],"Le,":[274],"Ld,":[275],"La,":[277],"gradually":[280],"corpora":[290],"maintaining":[292],"features.":[298],"Extensive":[299],"experimental":[300],"results":[301],"six":[303],"on":[306],"datasets,":[308],"Emo-DB,":[310],"eNTERFACE,":[311],"CASIA,":[313],"reveal":[314],"that":[315],"our":[316],"proposed":[317],"outperforms":[319],"state-of-the-art":[321],"methods.":[322]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-22T06:13:13.366637","created_date":"2025-10-10T00:00:00"}