{"id":"https://openalex.org/W3022013598","doi":"https://doi.org/10.1109/access.2020.2990405","title":"Clustering-Based Speech Emotion Recognition by Incorporating Learned Features and Deep BiLSTM","display_name":"Clustering-Based Speech Emotion Recognition by Incorporating Learned Features and Deep BiLSTM","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3022013598","doi":"https://doi.org/10.1109/access.2020.2990405","mag":"3022013598"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2990405","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2990405","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09078789.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_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,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09078789.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108128790","display_name":"Mustaqeem Mustaqeem","orcid":null},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Mustaqeem","raw_affiliation_strings":["Department of Software, Interaction Technology Laboratory, Sejong University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Software, Interaction Technology Laboratory, Sejong University, Seoul, South Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052654998","display_name":"Muhammad Sajjad","orcid":"https://orcid.org/0000-0001-5646-0338"},"institutions":[{"id":"https://openalex.org/I206573129","display_name":"Islamia College University","ror":"https://ror.org/02p2c1595","country_code":"PK","type":"education","lineage":["https://openalex.org/I206573129"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Sajjad","raw_affiliation_strings":["Department of Computer Science, Digital Image Processing Laboratory, Islamia College Peshawar, Peshawar, Pakistan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Digital Image Processing Laboratory, Islamia College Peshawar, Peshawar, Pakistan","institution_ids":["https://openalex.org/I206573129"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101836757","display_name":"Soonil Kwon","orcid":"https://orcid.org/0000-0001-5451-8815"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Soonil Kwon","raw_affiliation_strings":["Department of Software, Interaction Technology Laboratory, Sejong University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Software, Interaction Technology Laboratory, Sejong University, Seoul, South Korea","institution_ids":["https://openalex.org/I28777354"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5108128790"],"corresponding_institution_ids":["https://openalex.org/I28777354"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":41.8805,"has_fulltext":true,"cited_by_count":387,"citation_normalized_percentile":{"value":0.99900651,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"8","issue":null,"first_page":"79861","last_page":"79875"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9991999864578247,"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":0.9973000288009644,"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":0.841044008731842},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.7427037358283997},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6812962293624878},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5836905241012573},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5697163343429565},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5657451152801514},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.559180498123169},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5331315994262695},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.44772225618362427},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4468018412590027},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.43131542205810547}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.841044008731842},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.7427037358283997},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6812962293624878},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5836905241012573},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5697163343429565},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5657451152801514},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.559180498123169},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5331315994262695},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.44772225618362427},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4468018412590027},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.43131542205810547},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2990405","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2990405","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09078789.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_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,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:aad6bae5a7be4c7f9672598c1c0e07d2","is_oa":true,"landing_page_url":"https://doaj.org/article/aad6bae5a7be4c7f9672598c1c0e07d2","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 79861-79875 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2990405","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2990405","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09078789.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_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,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6700000166893005}],"awards":[{"id":"https://openalex.org/G3612847393","display_name":null,"funder_award_id":"2017-0-00189","funder_id":"https://openalex.org/F4320320729","funder_display_name":"Department of Information Technology, Ministry of Communications and Information Technology"},{"id":"https://openalex.org/G6072120315","display_name":null,"funder_award_id":"funded","funder_id":"https://openalex.org/F4320335489","funder_display_name":"Institute for Information and Communications Technology Promotion"},{"id":"https://openalex.org/G7685055460","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320320729","display_name":"Department of Information Technology, Ministry of Communications and Information Technology","ror":"https://ror.org/02z31cn83"},{"id":"https://openalex.org/F4320321287","display_name":"Sejong University","ror":"https://ror.org/00aft1q37"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"},{"id":"https://openalex.org/F4320335489","display_name":"Institute for Information and Communications Technology Promotion","ror":"https://ror.org/01g0hqq23"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3022013598.pdf","grobid_xml":"https://content.openalex.org/works/W3022013598.grobid-xml"},"referenced_works_count":73,"referenced_works":["https://openalex.org/W175750906","https://openalex.org/W1522301498","https://openalex.org/W1600744878","https://openalex.org/W1686810756","https://openalex.org/W2045528981","https://openalex.org/W2058580716","https://openalex.org/W2064675550","https://openalex.org/W2080289724","https://openalex.org/W2087618018","https://openalex.org/W2146334809","https://openalex.org/W2163605009","https://openalex.org/W2165306728","https://openalex.org/W2181741066","https://openalex.org/W2194775991","https://openalex.org/W2253716078","https://openalex.org/W2295001676","https://openalex.org/W2462044331","https://openalex.org/W2466877391","https://openalex.org/W2530421149","https://openalex.org/W2594395650","https://openalex.org/W2599621350","https://openalex.org/W2610961739","https://openalex.org/W2747298132","https://openalex.org/W2747506362","https://openalex.org/W2751683541","https://openalex.org/W2765860599","https://openalex.org/W2766272105","https://openalex.org/W2766756589","https://openalex.org/W2777468850","https://openalex.org/W2790117078","https://openalex.org/W2792362452","https://openalex.org/W2803193013","https://openalex.org/W2885005742","https://openalex.org/W2888786729","https://openalex.org/W2889544113","https://openalex.org/W2891540872","https://openalex.org/W2892071465","https://openalex.org/W2904753829","https://openalex.org/W2905917758","https://openalex.org/W2906725053","https://openalex.org/W2909327627","https://openalex.org/W2910444986","https://openalex.org/W2910655080","https://openalex.org/W2911220936","https://openalex.org/W2913795158","https://openalex.org/W2916370975","https://openalex.org/W2919464470","https://openalex.org/W2931501946","https://openalex.org/W2949248935","https://openalex.org/W2949471033","https://openalex.org/W2950846997","https://openalex.org/W2951123823","https://openalex.org/W2955805055","https://openalex.org/W2956824775","https://openalex.org/W2959133507","https://openalex.org/W2961638199","https://openalex.org/W2962843773","https://openalex.org/W2963670497","https://openalex.org/W2964370293","https://openalex.org/W2969889150","https://openalex.org/W2970737019","https://openalex.org/W2972811324","https://openalex.org/W2987850001","https://openalex.org/W2997700007","https://openalex.org/W3104223195","https://openalex.org/W6607193717","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6697498398","https://openalex.org/W6742726719","https://openalex.org/W6758876586","https://openalex.org/W6763271673"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W2011227383","https://openalex.org/W2088854863","https://openalex.org/W4402568167","https://openalex.org/W3179495260","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983"],"abstract_inverted_index":{"Emotional":[0],"state":[1,52,178],"recognition":[2,25,84,156,239],"of":[3,22,53,179,191,200,246,254],"a":[4,7,29,95,101,123],"speaker":[5],"is":[6,60,120,225,259],"difficult":[8],"task":[9],"for":[10,98,174],"machine":[11],"learning":[12],"algorithms":[13],"which":[14],"plays":[15,28],"an":[16,271],"important":[17],"role":[18,31],"in":[19,32,57,115],"the":[20,50,83,127,133,138,144,150,162,171,176,182,187,192,197,201,206,219,238,243,247,255,262],"field":[21,59],"speech":[23,79,145],"emotion":[24],"(SER).":[26],"SER":[27,99,257,268],"significant":[30],"many":[33],"real-time":[34],"applications":[35],"such":[36],"as":[37],"human":[38],"behavior":[39],"assessment,":[40],"human-robot":[41],"interaction,":[42],"virtual":[43],"reality,":[44],"and":[45,66,86,130,140,158,204,234,241,252,277,283],"emergency":[46],"centers":[47],"to":[48,74,81,136,153,161,169,195,236,266,274],"analyze":[49],"emotional":[51],"speakers.":[54],"Previous":[55],"research":[56],"this":[58],"mostly":[61],"focused":[62],"on":[63,107],"handcrafted":[64],"features":[65,77,142,152,208],"traditional":[67],"convolutional":[68],"neural":[69],"network":[70,111],"(CNN)":[71],"models":[72],"used":[73],"extract":[75,137],"high-level":[76],"from":[78,143,261],"spectrograms":[80],"increase":[82],"accuracy":[85,240,279],"overall":[87,202],"model":[88,135,203,258],"cost":[89],"complexity.":[90],"In":[91,181],"contrast,":[92],"we":[93,148,185],"introduce":[94],"novel":[96],"framework":[97],"using":[100],"key":[102,188],"sequence":[103,119],"segment":[104],"selection":[105],"based":[106,109],"redial":[108],"function":[110],"(RBFN)":[112],"similarity":[113],"measurement":[114],"clusters.":[116],"The":[117,222,250],"selected":[118],"converted":[121],"into":[122,132],"spectrogram":[124],"by":[125],"applying":[126],"STFT":[128],"algorithm":[129],"passed":[131],"CNN":[134,151,207],"discriminative":[139],"salient":[141],"spectrogram.":[146],"Furthermore,":[147],"normalize":[149,205],"ensure":[154],"precise":[155],"performance":[157],"feed":[159],"them":[160],"deep":[163],"bi-directional":[164],"long":[165],"short-term":[166],"memory":[167],"(BiLSTM)":[168],"learn":[170],"temporal":[172],"information":[173],"recognizing":[175],"final":[177],"emotion.":[180],"proposed":[183,223],"technique,":[184],"process":[186],"segments":[189],"instead":[190],"whole":[193],"utterance":[194],"reduce":[196,242],"computational":[198],"complexity":[199],"before":[209],"their":[210],"actual":[211],"processing,":[212],"so":[213],"that":[214],"it":[215],"can":[216],"easily":[217],"recognize":[218],"Spatio-temporal":[220],"information.":[221],"system":[224],"evaluated":[226],"over":[227,280],"different":[228],"standard":[229],"dataset":[230],"including":[231],"IEMOCAP,":[232,281],"EMO-DB,":[233,282],"RAVDESS":[235,284],"improve":[237],"processing":[244],"time":[245],"model,":[248],"respectively.":[249,286],"robustness":[251],"effectiveness":[253],"suggested":[256],"proved":[260],"experimentations":[263],"when":[264],"compared":[265],"state-of-the-art":[267],"methods":[269],"with":[270],"achieve":[272],"up":[273],"72.25%,":[275],"85.57%,":[276],"77.02%":[278],"dataset,":[285]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":55},{"year":2024,"cited_by_count":86},{"year":2023,"cited_by_count":95},{"year":2022,"cited_by_count":69},{"year":2021,"cited_by_count":54},{"year":2020,"cited_by_count":16}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}
