{"id":"https://openalex.org/W4405709341","doi":"https://doi.org/10.1109/iscslp63861.2024.10800413","title":"Speech Emotion Recognition Based on Shallow Structure of Wav2vec 2.0 and Attention Mechanism","display_name":"Speech Emotion Recognition Based on Shallow Structure of Wav2vec 2.0 and Attention Mechanism","publication_year":2024,"publication_date":"2024-11-07","ids":{"openalex":"https://openalex.org/W4405709341","doi":"https://doi.org/10.1109/iscslp63861.2024.10800413"},"language":"en","primary_location":{"id":"doi:10.1109/iscslp63861.2024.10800413","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscslp63861.2024.10800413","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 14th International Symposium on Chinese Spoken Language Processing (ISCSLP)","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/A5100632814","display_name":"Yumei Zhang","orcid":"https://orcid.org/0000-0002-6911-8694"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yumei Zhang","raw_affiliation_strings":["School of Information Science and Technology, Beijing University of Technology,Beijing"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Beijing University of Technology,Beijing","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000601742","display_name":"Maoshen Jia","orcid":"https://orcid.org/0000-0002-3452-3913"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Maoshen Jia","raw_affiliation_strings":["School of Information Science and Technology, Beijing University of Technology,Beijing"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Beijing University of Technology,Beijing","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113958844","display_name":"Xuan Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Cao","raw_affiliation_strings":["School of Information Science and Technology, Beijing University of Technology,Beijing"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Beijing University of Technology,Beijing","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101288224","display_name":"Zichen Zhao","orcid":"https://orcid.org/0009-0006-7132-3845"},"institutions":[{"id":"https://openalex.org/I1793135","display_name":"Yanbian University","ror":"https://ror.org/039xnh269","country_code":"CN","type":"education","lineage":["https://openalex.org/I1793135"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zichen Zhao","raw_affiliation_strings":["College of Engineering, Yanbian University,Yanji"],"affiliations":[{"raw_affiliation_string":"College of Engineering, Yanbian University,Yanji","institution_ids":["https://openalex.org/I1793135"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100632814"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29145064,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"398","last_page":"402"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13535","display_name":"Wireless Sensor Networks and IoT","score":0.5375999808311462,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13535","display_name":"Wireless Sensor Networks and IoT","score":0.5375999808311462,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12260","display_name":"Educational Technology and Pedagogy","score":0.5102999806404114,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.49219998717308044,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.7604170441627502},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.6635584235191345},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6593108773231506},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5342511534690857},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.36448195576667786}],"concepts":[{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.7604170441627502},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.6635584235191345},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6593108773231506},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5342511534690857},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.36448195576667786},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscslp63861.2024.10800413","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscslp63861.2024.10800413","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 14th International Symposium on Chinese Spoken Language Processing (ISCSLP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G310012415","display_name":null,"funder_award_id":"L233032,L223033","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G852593933","display_name":null,"funder_award_id":"62471012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W99444952","https://openalex.org/W175750906","https://openalex.org/W2085662862","https://openalex.org/W2104074072","https://openalex.org/W2146334809","https://openalex.org/W2767087747","https://openalex.org/W2887783524","https://openalex.org/W2905054565","https://openalex.org/W2973037561","https://openalex.org/W2996906606","https://openalex.org/W3040201034","https://openalex.org/W3132302778","https://openalex.org/W3162475537","https://openalex.org/W3169022486","https://openalex.org/W3186351311","https://openalex.org/W3197156295","https://openalex.org/W3197642003","https://openalex.org/W3208480086","https://openalex.org/W3210971248","https://openalex.org/W4206326349","https://openalex.org/W4230277160","https://openalex.org/W4319596491","https://openalex.org/W4319862479","https://openalex.org/W4352977805","https://openalex.org/W4360856918","https://openalex.org/W4379033883","https://openalex.org/W4386176982","https://openalex.org/W4390874621","https://openalex.org/W6862245598"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W3126677997","https://openalex.org/W1610857240"],"abstract_inverted_index":{"Speech":[0],"Emotion":[1],"Recognition":[2],"(SER)":[3],"has":[4],"always":[5],"been":[6,50],"an":[7],"important":[8],"topic":[9],"in":[10,30],"the":[11,18,58,63,83,86,92,101,125,130,151,158,161],"field":[12],"of":[13,17,66,85,89,106],"human-computer":[14],"interaction.":[15],"Most":[16],"existing":[19],"methods":[20],"use":[21],"handcrafted":[22],"features,":[23],"which":[24],"may":[25],"ignore":[26],"emotion-related":[27],"information":[28,128],"contained":[29],"raw":[31,114],"speech":[32,37,55,115],"signals.":[33,116],"In":[34,74],"recent":[35],"years,":[36],"Self-supervised":[38],"Learning":[39],"(SSL)":[40],"models":[41,71],"such":[42],"as":[43],"Wav2vec":[44],"2.0":[45],"(W2V2)":[46],"have":[47],"emerged":[48],"and":[49,91,163],"employed":[51],"to":[52,108,122],"extract":[53,109],"general":[54],"representations":[56,112],"for":[57,143],"downstream":[59],"SER":[60,78],"tasks.":[61],"However,":[62],"large":[64],"number":[65],"parameters":[67],"introduced":[68],"by":[69],"SSL":[70],"is":[72,80,98,120],"unnecessary.":[73],"this":[75,135],"paper,":[76],"a":[77],"model":[79,153],"proposed":[81,152],"on":[82,160],"basis":[84],"shallow":[87],"structure":[88],"W2V2":[90,107],"attention":[93],"mechanism.":[94],"The":[95,117],"W2V2-based":[96],"module":[97,119],"constructed":[99],"using":[100],"first":[102],"seven":[103],"Conv1d":[104],"blocks":[105,140],"local":[110,131],"feature":[111,132,145],"from":[113,129],"attention-based":[118],"used":[121],"globally":[123],"capture":[124],"contextual":[126],"emotional":[127],"representations.":[133],"Within":[134],"module,":[136],"three":[137],"multi-head":[138],"self-attention":[139],"are":[141],"cascaded":[142],"multilevel":[144],"fusion.":[146],"Experimental":[147],"results":[148],"show":[149],"that":[150],"achieves":[154],"better":[155],"performance":[156],"than":[157],"baselines":[159],"IEMOCAP":[162],"EMODB":[164],"datasets.":[165]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}