{"id":"https://openalex.org/W3144907487","doi":"https://doi.org/10.1109/access.2021.3069818","title":"Autoencoder With Emotion Embedding for Speech Emotion Recognition","display_name":"Autoencoder With Emotion Embedding for Speech Emotion Recognition","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3144907487","doi":"https://doi.org/10.1109/access.2021.3069818","mag":"3144907487"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3069818","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09389805.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09389805.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052229375","display_name":"Chenghao Zhang","orcid":"https://orcid.org/0000-0002-9925-0848"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"funder","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenghao Zhang","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027964223","display_name":"Lei Xue","orcid":"https://orcid.org/0000-0002-4236-8714"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"funder","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Xue","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.621,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":43,"citation_normalized_percentile":{"value":0.849401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"9","issue":null,"first_page":"51231","last_page":"51241"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9997,"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":0.9997,"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/T10860","display_name":"Speech and Audio Processing","score":0.9989,"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/T11309","display_name":"Music and Audio Processing","score":0.9983,"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/autoencoder","display_name":"Autoencoder","score":0.8991364},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization","score":0.6374309},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature Learning","score":0.49126238}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8991364},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.80678666},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6374309},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5828941},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5287825},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.49126238},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.45983833},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4436442},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.42845994},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.38472095},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35847214},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3069818","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09389805.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},{"is_oa":false,"landing_page_url":"https://doaj.org/article/c450ff0b8658435c9e31592597dab594","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":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3069818","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09389805.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_indexed_in_scopus":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":76,"referenced_works":["https://openalex.org/W101583998","https://openalex.org/W147964346","https://openalex.org/W1501669607","https://openalex.org/W1611652295","https://openalex.org/W175750906","https://openalex.org/W1836465849","https://openalex.org/W1922655562","https://openalex.org/W1989674786","https://openalex.org/W2016891207","https://openalex.org/W2032254851","https://openalex.org/W2042970394","https://openalex.org/W2049462786","https://openalex.org/W2060470614","https://openalex.org/W2062391442","https://openalex.org/W2071712938","https://openalex.org/W2074788634","https://openalex.org/W2085662862","https://openalex.org/W2099621636","https://openalex.org/W2111926505","https://openalex.org/W2146334809","https://openalex.org/W2157331557","https://openalex.org/W2162514423","https://openalex.org/W2169891262","https://openalex.org/W2184343439","https://openalex.org/W2194775991","https://openalex.org/W2398146340","https://openalex.org/W2407080277","https://openalex.org/W2408520939","https://openalex.org/W2463355599","https://openalex.org/W2502312327","https://openalex.org/W2511508976","https://openalex.org/W2512449761","https://openalex.org/W2526834636","https://openalex.org/W2533262878","https://openalex.org/W2545656684","https://openalex.org/W2560574036","https://openalex.org/W2572730214","https://openalex.org/W2583643061","https://openalex.org/W2603777577","https://openalex.org/W2605045867","https://openalex.org/W2614874155","https://openalex.org/W2617258110","https://openalex.org/W2749881488","https://openalex.org/W2766736793","https://openalex.org/W2785044468","https://openalex.org/W2786857286","https://openalex.org/W2795986449","https://openalex.org/W2803098682","https://openalex.org/W2884366600","https://openalex.org/W2889544113","https://openalex.org/W2896457183","https://openalex.org/W2898276184","https://openalex.org/W2914132458","https://openalex.org/W2923871787","https://openalex.org/W2936451900","https://openalex.org/W2936774411","https://openalex.org/W2940259008","https://openalex.org/W2949117887","https://openalex.org/W2951442257","https://openalex.org/W2951684117","https://openalex.org/W2954676478","https://openalex.org/W2962739339","https://openalex.org/W2963073614","https://openalex.org/W2963087613","https://openalex.org/W2963403868","https://openalex.org/W2963609956","https://openalex.org/W2964328256","https://openalex.org/W2971275122","https://openalex.org/W2972724712","https://openalex.org/W2972852081","https://openalex.org/W2998704965","https://openalex.org/W3015141382","https://openalex.org/W3046556784","https://openalex.org/W3082675846","https://openalex.org/W4285719527","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W4389832810","https://openalex.org/W4313561566","https://openalex.org/W4281663961","https://openalex.org/W4220682630","https://openalex.org/W3208888551","https://openalex.org/W3208386644","https://openalex.org/W3181622257","https://openalex.org/W3163146846","https://openalex.org/W2983142544","https://openalex.org/W2891059443"],"abstract_inverted_index":{"An":[0],"important":[1],"part":[2],"of":[3,27,48,169],"the":[4,39,45,49,89,103,112,121,126,140,145,152,156,167,199],"human-computer":[5],"interaction":[6],"process":[7],"is":[8,52,84,93,160,177],"speech":[9,209],"emotion":[10,70,75,104,163,210],"recognition":[11,211],"(SER),":[12],"which":[13,83,130],"has":[14,29],"been":[15,30],"receiving":[16],"more":[17],"attention":[18],"in":[19,32,44,88,107],"recent":[20],"years.":[21],"However,":[22],"although":[23],"a":[24,64,85,117,172],"wide":[25],"diversity":[26],"methods":[28],"proposed":[31,200],"SER,":[33],"these":[34],"approaches":[35],"still":[36],"cannot":[37],"improve":[38,166],"performance.":[40],"A":[41],"key":[42],"issue":[43],"low":[46],"performance":[47,204],"SER":[50],"system":[51],"how":[53],"to":[54,72,114,128,135,191,207],"effectively":[55],"extract":[56,73],"emotion-oriented":[57],"features.":[58,76],"In":[59],"this":[60],"paper,":[61],"we":[62],"propose":[63],"novel":[65],"algorithm,":[66],"an":[67],"autoencoder":[68,113,146],"with":[69],"embedding,":[71],"deep":[74],"Unlike":[77],"many":[78],"previous":[79],"works,":[80],"instance":[81],"normalization,":[82],"common":[86],"technique":[87],"style":[90],"transfer":[91],"field,":[92],"introduced":[94],"into":[95],"our":[96,108,170,193],"model":[97,127,201],"rather":[98],"than":[99],"batch":[100],"normalization.":[101],"Furthermore,":[102],"embedding":[105],"path":[106],"method":[109],"can":[110,124],"lead":[111],"efficiently":[115],"learn":[116],"priori":[118],"knowledge":[119],"from":[120],"label.":[122],"It":[123],"enable":[125],"distinguish":[129],"features":[131,149],"are":[132,189],"most":[133],"related":[134],"human":[136],"emotion.":[137],"We":[138],"concatenate":[139],"latent":[141],"representation":[142],"learned":[143],"by":[144,151],"and":[147,182,187],"acoustic":[148],"obtained":[150],"openSMILE":[153],"toolkit.":[154],"Finally,":[155],"concatenated":[157],"feature":[158],"vector":[159],"utilized":[161],"for":[162],"classification.":[164],"To":[165],"generalization":[168],"method,":[171],"simple":[173],"data":[174],"augmentation":[175],"approach":[176],"applied.":[178],"Two":[179],"publicly":[180],"available":[181],"highly":[183],"popular":[184],"databases,":[185],"IEMOCAP":[186],"EMODB,":[188],"chosen":[190],"evaluate":[192],"method.":[194],"Experimental":[195],"results":[196],"demonstrate":[197],"that":[198],"achieves":[202],"significant":[203],"improvement":[205],"compared":[206],"other":[208],"systems.":[212]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3144907487","counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":11}],"updated_date":"2025-05-01T15:13:42.364201","created_date":"2021-04-13"}