{"id":"https://openalex.org/W4285093204","doi":"https://doi.org/10.3390/sym14071428","title":"Multi-Task Conformer with Multi-Feature Combination for Speech Emotion Recognition","display_name":"Multi-Task Conformer with Multi-Feature Combination for Speech Emotion Recognition","publication_year":2022,"publication_date":"2022-07-12","ids":{"openalex":"https://openalex.org/W4285093204","doi":"https://doi.org/10.3390/sym14071428"},"language":"en","primary_location":{"id":"doi:10.3390/sym14071428","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14071428","pdf_url":"https://www.mdpi.com/2073-8994/14/7/1428/pdf?version=1657613202","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/14/7/1428/pdf?version=1657613202","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025852861","display_name":"Jiyoung Seo","orcid":"https://orcid.org/0000-0002-0998-5083"},"institutions":[{"id":"https://openalex.org/I191879574","display_name":"Inha University","ror":"https://ror.org/01easw929","country_code":"KR","type":"education","lineage":["https://openalex.org/I191879574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jiyoung Seo","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Korea","institution_ids":["https://openalex.org/I191879574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089545632","display_name":"Bowon Lee","orcid":"https://orcid.org/0000-0001-5417-5699"},"institutions":[{"id":"https://openalex.org/I191879574","display_name":"Inha University","ror":"https://ror.org/01easw929","country_code":"KR","type":"education","lineage":["https://openalex.org/I191879574"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Bowon Lee","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Korea","institution_ids":["https://openalex.org/I191879574"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089545632"],"corresponding_institution_ids":["https://openalex.org/I191879574"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":4.2544,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.94625648,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"14","issue":"7","first_page":"1428","last_page":"1428"},"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/T11309","display_name":"Music and Audio Processing","score":0.9973000288009644,"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":0.9969000220298767,"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/computer-science","display_name":"Computer science","score":0.7149348258972168},{"id":"https://openalex.org/keywords/arousal","display_name":"Arousal","score":0.6901125907897949},{"id":"https://openalex.org/keywords/valence","display_name":"Valence (chemistry)","score":0.6887156367301941},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.661630392074585},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.6075952053070068},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.5964914560317993},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5943751335144043},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4807700514793396},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42508822679519653},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.418559730052948},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.41323524713516235},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.36961835622787476},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.20132100582122803},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.19860002398490906}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7149348258972168},{"id":"https://openalex.org/C36951298","wikidata":"https://www.wikidata.org/wiki/Q379784","display_name":"Arousal","level":2,"score":0.6901125907897949},{"id":"https://openalex.org/C168900304","wikidata":"https://www.wikidata.org/wiki/Q171407","display_name":"Valence (chemistry)","level":2,"score":0.6887156367301941},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.661630392074585},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.6075952053070068},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.5964914560317993},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5943751335144043},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4807700514793396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42508822679519653},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.418559730052948},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.41323524713516235},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36961835622787476},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20132100582122803},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.19860002398490906},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym14071428","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14071428","pdf_url":"https://www.mdpi.com/2073-8994/14/7/1428/pdf?version=1657613202","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d0f37cec70df414382c33fd0ac25ea6f","is_oa":true,"landing_page_url":"https://doaj.org/article/d0f37cec70df414382c33fd0ac25ea6f","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 14, Iss 7, p 1428 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/14/7/1428/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym14071428","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":"Symmetry","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym14071428","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym14071428","pdf_url":"https://www.mdpi.com/2073-8994/14/7/1428/pdf?version=1657613202","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285093204.pdf","grobid_xml":"https://content.openalex.org/works/W4285093204.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W15066456","https://openalex.org/W204722540","https://openalex.org/W2009059481","https://openalex.org/W2055332436","https://openalex.org/W2083638007","https://openalex.org/W2115144768","https://openalex.org/W2146334809","https://openalex.org/W2191779130","https://openalex.org/W2295001676","https://openalex.org/W2343758848","https://openalex.org/W2747172199","https://openalex.org/W2801768581","https://openalex.org/W2807062934","https://openalex.org/W2890964092","https://openalex.org/W2936774411","https://openalex.org/W2937977583","https://openalex.org/W2939765894","https://openalex.org/W2963182768","https://openalex.org/W2963846422","https://openalex.org/W2964243274","https://openalex.org/W2970737019","https://openalex.org/W2972602947","https://openalex.org/W2999713883","https://openalex.org/W3015141382","https://openalex.org/W3015267357","https://openalex.org/W3015826515","https://openalex.org/W3097777922","https://openalex.org/W3114925916","https://openalex.org/W3120680448","https://openalex.org/W3160525311","https://openalex.org/W3161659450","https://openalex.org/W3206495532","https://openalex.org/W4205567678","https://openalex.org/W4224234075","https://openalex.org/W6739901393","https://openalex.org/W6761305474","https://openalex.org/W6775408604"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W2900413183","https://openalex.org/W3022252430","https://openalex.org/W4390975304","https://openalex.org/W4287804464","https://openalex.org/W3103989898","https://openalex.org/W3211292372","https://openalex.org/W803346624"],"abstract_inverted_index":{"Along":[0],"with":[1],"automatic":[2],"speech":[3,11,110],"recognition,":[4,13],"many":[5],"researchers":[6],"have":[7],"been":[8],"actively":[9],"studying":[10],"emotion":[12,15,33,39,111],"since":[14],"information":[16,23,55],"is":[17,40],"as":[18,20,47,78,85,92],"crucial":[19],"the":[21,57,137],"textual":[22],"for":[24,69,109,129],"effective":[25],"interactions.":[26],"Emotion":[27],"can":[28,51],"be":[29],"divided":[30],"into":[31],"categorical":[32,38],"and":[34,49,71,88,101,113],"dimensional":[35,43],"emotion.":[36],"Although":[37],"widely":[41],"used,":[42],"emotion,":[44],"typically":[45],"represented":[46],"arousal":[48,70,130],"valence,":[50],"provide":[52],"more":[53],"detailed":[54],"on":[56,136],"emotional":[58],"states.":[59],"Therefore,":[60],"in":[61,131],"this":[62],"paper,":[63],"we":[64,97],"propose":[65],"a":[66,81,86,93,106,121],"Conformer-based":[67],"model":[68,75,119],"valence":[72],"recognition.":[73],"Our":[74],"uses":[76],"Conformer":[77],"an":[79],"encoder,":[80],"fully":[82],"connected":[83],"layer":[84],"decoder,":[87],"statistical":[89],"pooling":[90],"layers":[91],"connector.":[94],"In":[95],"addition,":[96],"adopted":[98],"multi-task":[99],"learning":[100],"multi-feature":[102],"combination,":[103],"which":[104],"showed":[105],"remarkable":[107],"performance":[108],"recognition":[112,123],"time-series":[114],"analysis,":[115],"respectively.":[116],"The":[117],"proposed":[118],"achieves":[120],"state-of-the-art":[122],"accuracy":[124,135],"of":[125,133],"70.0":[126],"\u00b1":[127],"1.5%":[128],"terms":[132],"unweighted":[134],"IEMOCAP":[138],"dataset.":[139]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
