{"id":"https://openalex.org/W3011995592","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023339","title":"Speaker to Emotion: Domain Adaptation for Speech Emotion Recognition with Residual Adapters","display_name":"Speaker to Emotion: Domain Adaptation for Speech Emotion Recognition with Residual Adapters","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3011995592","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023339","mag":"3011995592"},"language":"en","primary_location":{"id":"doi:10.1109/apsipaasc47483.2019.9023339","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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/A5008878112","display_name":"Yuxuan Xi","orcid":"https://orcid.org/0009-0004-6234-130X"},"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":true,"raw_author_name":"Yuxuan Xi","raw_affiliation_strings":["National Engineering Laboratory of Speech and Language Information Processing, University of Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory of Speech and Language Information Processing, University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101644250","display_name":"Pengcheng Li","orcid":"https://orcid.org/0009-0007-5302-9105"},"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":"Pengcheng Li","raw_affiliation_strings":["National Engineering Laboratory of Speech and Language Information Processing, University of Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory of Speech and Language Information Processing, University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100381758","display_name":"Yan Song","orcid":"https://orcid.org/0000-0002-5668-9068"},"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":["National Engineering Laboratory of Speech and Language Information Processing, University of Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory of Speech and Language Information Processing, University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014118765","display_name":"Yiheng Jiang","orcid":null},"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":"Yiheng Jiang","raw_affiliation_strings":["National Engineering Laboratory of Speech and Language Information Processing, University of Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory of Speech and Language Information Processing, University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057227915","display_name":"Li-Rong Dai","orcid":"https://orcid.org/0000-0002-0859-2827"},"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":"Lirong Dai","raw_affiliation_strings":["National Engineering Laboratory of Speech and Language Information Processing, University of Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory of Speech and Language Information Processing, University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5008878112"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":2.2324,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.88526027,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"2019","issue":null,"first_page":"513","last_page":"518"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9994999766349792,"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":0.9988999962806702,"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":0.8494880199432373},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6888520121574402},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.5678130388259888},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.5399124622344971},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5297359228134155},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5005652904510498},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.499377965927124},{"id":"https://openalex.org/keywords/adapter","display_name":"Adapter (computing)","score":0.4860242009162903},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.4623843729496002},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4539366662502289},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.45012640953063965},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40801069140434265}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8494880199432373},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6888520121574402},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.5678130388259888},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.5399124622344971},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5297359228134155},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5005652904510498},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.499377965927124},{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.4860242009162903},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.4623843729496002},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4539366662502289},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.45012640953063965},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40801069140434265},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/apsipaasc47483.2019.9023339","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023339","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"},{"id":"mag:3087663052","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002287335078186","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W175750906","https://openalex.org/W1501669607","https://openalex.org/W1581984155","https://openalex.org/W1836465849","https://openalex.org/W2054857826","https://openalex.org/W2146334809","https://openalex.org/W2194775991","https://openalex.org/W2295001676","https://openalex.org/W2322208196","https://openalex.org/W2400814905","https://openalex.org/W2408520939","https://openalex.org/W2510170536","https://openalex.org/W2589599921","https://openalex.org/W2598545578","https://openalex.org/W2599621350","https://openalex.org/W2616957565","https://openalex.org/W2648194195","https://openalex.org/W2747664154","https://openalex.org/W2761514455","https://openalex.org/W2795986449","https://openalex.org/W2801705442","https://openalex.org/W2802656254","https://openalex.org/W2808631503","https://openalex.org/W2886300652","https://openalex.org/W2889374687","https://openalex.org/W2889507358","https://openalex.org/W2889544113","https://openalex.org/W2894458059","https://openalex.org/W2962839749","https://openalex.org/W2963211188","https://openalex.org/W6607193717","https://openalex.org/W6697498398","https://openalex.org/W6714031499","https://openalex.org/W6751469484","https://openalex.org/W6751901074","https://openalex.org/W6754641952"],"related_works":["https://openalex.org/W2807901368","https://openalex.org/W2158491338","https://openalex.org/W2118039276","https://openalex.org/W3006475563","https://openalex.org/W3015707499","https://openalex.org/W2049462786","https://openalex.org/W4287868249","https://openalex.org/W2326728821","https://openalex.org/W4297798768","https://openalex.org/W1604435341"],"abstract_inverted_index":{"Despite":[0],"considerable":[1],"recent":[2],"progress":[3],"in":[4,159],"deep":[5],"learning":[6],"methods":[7],"for":[8,55,72,100,111,128],"speech":[9,23,74],"emotion":[10,24,75,91],"recognition":[11,76],"(SER),":[12],"performance":[13],"is":[14,29,70,98],"severely":[15],"restricted":[16],"by":[17,42],"the":[18,56,73,101,129,135,138],"lack":[19],"of":[20,137],"large-scale":[21],"labeled":[22],"corpora.":[25,151],"For":[26],"instance,":[27],"it":[28],"difficult":[30],"to":[31,52,81,89,123],"employ":[32],"complex":[33],"neural":[34],"network":[35],"architectures":[36],"such":[37],"as":[38,107],"ResNet,":[39],"which":[40,79],"accompanied":[41],"large-sale":[43],"corpora":[44],"like":[45],"VoxCeleb":[46],"and":[47,148],"NIST":[48],"SRE,":[49],"have":[50],"proven":[51],"perform":[53],"well":[54],"related":[57,83],"speaker":[58,87],"verification":[59],"(SV)":[60],"task.":[61,132],"In":[62],"this":[63],"paper,":[64],"a":[65,86,94,108],"novel":[66],"domain":[67],"adaptation":[68],"method":[69],"proposed":[71,139],"(SER)":[77],"task,":[78],"aims":[80],"transfer":[82],"information":[84,113],"from":[85],"corpus":[88],"an":[90],"corpus.":[92],"Specifically,":[93],"residual":[95],"adapter":[96,116],"architecture":[97],"designed":[99],"SER":[102,131],"task":[103,161],"where":[104],"ResNet":[105],"acts":[106],"universal":[109],"model":[110],"general":[112],"extraction.":[114],"An":[115],"module":[117],"then":[118],"trains":[119],"limited":[120],"additional":[121],"parameters":[122],"focus":[124],"on":[125,145],"modeling":[126],"deviation":[127],"specific":[130],"To":[133],"evaluate":[134],"effectiveness":[136],"method,":[140],"we":[141],"conduct":[142],"extensive":[143],"evaluations":[144],"benchmark":[146],"IEMOCAP":[147],"CHEAVD":[149],"2.0":[150],"Results":[152],"show":[153],"significant":[154],"improvement,":[155],"with":[156],"overall":[157],"results":[158],"each":[160],"outperforming":[162],"or":[163],"matching":[164],"state-of-the-art":[165],"methods.":[166]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}