{"id":"https://openalex.org/W4416799176","doi":"https://doi.org/10.1109/apsipaasc65261.2025.11249205","title":"An Efficient Transfer Learning Method Based on Adapter with Local Attributes for Speech Emotion Recognition","display_name":"An Efficient Transfer Learning Method Based on Adapter with Local Attributes for Speech Emotion Recognition","publication_year":2025,"publication_date":"2025-10-22","ids":{"openalex":"https://openalex.org/W4416799176","doi":"https://doi.org/10.1109/apsipaasc65261.2025.11249205"},"language":null,"primary_location":{"id":"doi:10.1109/apsipaasc65261.2025.11249205","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc65261.2025.11249205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5026896241","display_name":"Haoyu Song","orcid":"https://orcid.org/0000-0001-5377-6628"},"institutions":[{"id":"https://openalex.org/I168639165","display_name":"Singapore Institute of Technology","ror":"https://ror.org/01v2c2791","country_code":"SG","type":"education","lineage":["https://openalex.org/I168639165"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Haoyu Song","raw_affiliation_strings":["Singapore Institute of Technology,Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Singapore Institute of Technology,Singapore","institution_ids":["https://openalex.org/I168639165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000620878","display_name":"Ian McLoughlin","orcid":"https://orcid.org/0000-0001-7111-2008"},"institutions":[{"id":"https://openalex.org/I168639165","display_name":"Singapore Institute of Technology","ror":"https://ror.org/01v2c2791","country_code":"SG","type":"education","lineage":["https://openalex.org/I168639165"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Ian McLoughlin","raw_affiliation_strings":["Singapore Institute of Technology,Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Singapore Institute of Technology,Singapore","institution_ids":["https://openalex.org/I168639165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024339730","display_name":"Qing Gu","orcid":"https://orcid.org/0000-0003-3855-3690"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Gu","raw_affiliation_strings":["School of Information Science and Technology, University of Science and Technology of China,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, University of Science and Technology of China,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114949056","display_name":"Nan Jiang","orcid":"https://orcid.org/0000-0002-5337-890X"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nan Jiang","raw_affiliation_strings":["School of Information Science and Technology, University of Science and Technology of China,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, University of Science and Technology of China,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046829204","display_name":"Yan Song","orcid":"https://orcid.org/0000-0002-9035-9142"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Song","raw_affiliation_strings":["School of Information Science and Technology, University of Science and Technology of China,Hefei,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, University of Science and Technology of China,Hefei,China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34706593,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"736","last_page":"740"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9804999828338623,"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":0.9804999828338623,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.004399999976158142,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.002899999963119626,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adapter","display_name":"Adapter (computing)","score":0.7152000069618225},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6491000056266785},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5641000270843506},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5613999962806702},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.5051000118255615},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4690999984741211},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.4154999852180481}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7935000061988831},{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.7152000069618225},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6491000056266785},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5641000270843506},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5613999962806702},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.536300003528595},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.5051000118255615},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.49559998512268066},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4690999984741211},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.4154999852180481},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4153999984264374},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.40459999442100525},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.396699994802475},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37209999561309814},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.37139999866485596},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3517000079154968},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C88548561","wikidata":"https://www.wikidata.org/wiki/Q347599","display_name":"sort","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipaasc65261.2025.11249205","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc65261.2025.11249205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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":22,"referenced_works":["https://openalex.org/W1987048275","https://openalex.org/W2137639365","https://openalex.org/W2146334809","https://openalex.org/W2160815625","https://openalex.org/W2972452068","https://openalex.org/W3019352575","https://openalex.org/W3093895424","https://openalex.org/W3162950882","https://openalex.org/W3197642003","https://openalex.org/W3209059054","https://openalex.org/W4221162793","https://openalex.org/W4221162872","https://openalex.org/W4224918285","https://openalex.org/W4224979832","https://openalex.org/W4297841446","https://openalex.org/W4312804044","https://openalex.org/W4313156423","https://openalex.org/W4372261521","https://openalex.org/W4372270299","https://openalex.org/W4385823319","https://openalex.org/W4390414889","https://openalex.org/W4402112331"],"related_works":[],"abstract_inverted_index":{"Existing":[0],"speech":[1,44],"emotion":[2,23],"recognition":[3],"(SER)":[4],"methods":[5,36,227],"commonly":[6],"suffer":[7],"from":[8,152,165],"the":[9,18,39,118,133,146,153,166,201,204,224],"lack":[10],"of":[11,22,67,203],"high-quality":[12],"large-scale":[13,43],"corpus,":[14],"partly":[15],"due":[16],"to":[17,73,93,116,174,193,223],"complex,":[19],"psychological":[20],"nature":[21],"which":[24,172],"makes":[25],"accurate":[26],"labeling":[27],"difficult":[28],"and":[29,48,71,142,145],"time":[30],"consuming.":[31],"Recently,":[32],"transfer":[33,102,130],"learning":[34],"based":[35],"that":[37,180],"exploit":[38],"encoders":[40],"pretrained":[41],"on":[42,215],"corpus":[45],"(e.g.,":[46],"Wav2Vec2.0":[47],"HuBERT)":[49],"have":[50,212],"shown":[51],"strong":[52],"potential":[53],"for":[54,63,83,100,128,197],"downstream":[55],"SER":[56,85],"tasks.":[57,86],"However,":[58],"task-specific":[59],"finetuning":[60],"remains":[61],"necessary":[62],"various":[64],"conversational":[65],"scenarios":[66],"different":[68],"topics,":[69],"speakers":[70],"languages":[72],"achieve":[74],"satisfactory":[75],"performance.":[76],"It":[77],"generally":[78],"requires":[79],"costly":[80],"encoder":[81],"retraining":[82],"individual":[84],"To":[87,199],"address":[88],"this":[89],"issue,":[90],"we":[91],"propose":[92],"train":[94],"an":[95],"adapter":[96,122,206],"with":[97,123,207],"local":[98,161,208],"attributes":[99,162],"efficient":[101],"learning.":[103],"Specifically,":[104],"a":[105,113,177],"weighted":[106],"average":[107,158],"pooling-Transformer":[108],"(WAP-Transformer)":[109],"is":[110,126,136,149,191],"proposed":[111,192,205],"as":[112,176],"lightweight":[114],"backbone":[115],"enrich":[117],"frame-level":[119],"representation.":[120],"An":[121],"teacher-student":[124],"branches":[125],"exploited":[127],"task-agnostic":[129],"learning,":[131],"where":[132],"student":[134,154],"branch":[135,148,168],"jointly":[137],"optimized":[138],"via":[139,155,169],"mask":[140],"prediction":[141],"self-distillation":[143],"objectives,":[144],"teacher":[147,167],"obtained":[150],"online":[151],"exponential":[156],"moving":[157],"(EMA).":[159],"Meanwhile,":[160],"are":[163],"learned":[164],"unsupervised":[170],"clustering,":[171],"aims":[173],"act":[175],"universal":[178],"model":[179],"provides":[181],"additional":[182],"semantic-rich":[183],"supervisions.":[184],"A":[185],"statistical":[186],"attentive":[187],"pooling":[188],"(SAP)":[189],"module":[190],"obtain":[194],"utterance":[195],"representation":[196],"finetuning.":[198],"evaluate":[200],"effectiveness":[202],"attributes,":[209],"extensive":[210],"experiments":[211],"been":[213,220],"conducted":[214],"IEMOCAP.":[216],"Superior":[217],"performance":[218],"has":[219],"reported,":[221],"compared":[222],"previous":[225],"state-of-the-art":[226],"in":[228],"similar":[229],"settings.":[230]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-28T00:00:00"}