{"id":"https://openalex.org/W3084484668","doi":"https://doi.org/10.3390/s20185212","title":"Deep-Net: A Lightweight CNN-Based Speech Emotion Recognition System Using Deep Frequency Features","display_name":"Deep-Net: A Lightweight CNN-Based Speech Emotion Recognition System Using Deep Frequency Features","publication_year":2020,"publication_date":"2020-09-12","ids":{"openalex":"https://openalex.org/W3084484668","doi":"https://doi.org/10.3390/s20185212","mag":"3084484668","pmid":"https://pubmed.ncbi.nlm.nih.gov/32932723"},"language":"en","primary_location":{"id":"doi:10.3390/s20185212","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20185212","pdf_url":"https://www.mdpi.com/1424-8220/20/18/5212/pdf?version=1600247647","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"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":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/20/18/5212/pdf?version=1600247647","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030335452","display_name":"Anvarjon Tursunov","orcid":"https://orcid.org/0000-0002-7419-494X"},"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":"Tursunov Anvarjon","raw_affiliation_strings":["Interaction Technology Laboratory, Department of Software, Sejong University, Seoul 05006, Korea"],"affiliations":[{"raw_affiliation_string":"Interaction Technology Laboratory, Department of Software, Sejong University, Seoul 05006, Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","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":false,"raw_author_name":"Mustaqeem","raw_affiliation_strings":["Interaction Technology Laboratory, Department of Software, Sejong University, Seoul 05006, Korea"],"affiliations":[{"raw_affiliation_string":"Interaction Technology Laboratory, Department of Software, Sejong University, Seoul 05006, Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"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":true,"raw_author_name":"Soonil Kwon","raw_affiliation_strings":["Interaction Technology Laboratory, Department of Software, Sejong University, Seoul 05006, Korea"],"affiliations":[{"raw_affiliation_string":"Interaction Technology Laboratory, Department of Software, Sejong University, Seoul 05006, Korea","institution_ids":["https://openalex.org/I28777354"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101836757"],"corresponding_institution_ids":["https://openalex.org/I28777354"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":17.7166,"has_fulltext":false,"cited_by_count":165,"citation_normalized_percentile":{"value":0.99472827,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"20","issue":"18","first_page":"5212","last_page":"5212"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":1.0,"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":1.0,"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":0.9972000122070312,"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":0.9955000281333923,"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":0.7773420810699463},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7005451917648315},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5883695483207703},{"id":"https://openalex.org/keywords/disgust","display_name":"Disgust","score":0.5773680806159973},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5615524649620056},{"id":"https://openalex.org/keywords/sadness","display_name":"Sadness","score":0.5407301187515259},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5239279866218567},{"id":"https://openalex.org/keywords/surprise","display_name":"Surprise","score":0.4578917920589447},{"id":"https://openalex.org/keywords/boredom","display_name":"Boredom","score":0.4461287260055542},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.43989771604537964},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.42818695306777954},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.41026031970977783},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.4087620675563812}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7773420810699463},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7005451917648315},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5883695483207703},{"id":"https://openalex.org/C2777375102","wikidata":"https://www.wikidata.org/wiki/Q208351","display_name":"Disgust","level":3,"score":0.5773680806159973},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5615524649620056},{"id":"https://openalex.org/C2779812673","wikidata":"https://www.wikidata.org/wiki/Q169251","display_name":"Sadness","level":3,"score":0.5407301187515259},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5239279866218567},{"id":"https://openalex.org/C2780343955","wikidata":"https://www.wikidata.org/wiki/Q333173","display_name":"Surprise","level":2,"score":0.4578917920589447},{"id":"https://openalex.org/C2777589236","wikidata":"https://www.wikidata.org/wiki/Q34255","display_name":"Boredom","level":2,"score":0.4461287260055542},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.43989771604537964},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.42818695306777954},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.41026031970977783},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.4087620675563812},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004644","descriptor_name":"Emotions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004644","descriptor_name":"Emotions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004644","descriptor_name":"Emotions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004644","descriptor_name":"Emotions","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013060","descriptor_name":"Speech","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D013060","descriptor_name":"Speech","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D013060","descriptor_name":"Speech","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D013060","descriptor_name":"Speech","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s20185212","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20185212","pdf_url":"https://www.mdpi.com/1424-8220/20/18/5212/pdf?version=1600247647","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"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":"Sensors","raw_type":"journal-article"},{"id":"pmid:32932723","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/32932723","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:ce0971595d2b4cf3a936c57557e84284","is_oa":true,"landing_page_url":"https://doaj.org/article/ce0971595d2b4cf3a936c57557e84284","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":"Sensors, Vol 20, Iss 18, p 5212 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/20/18/5212/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s20185212","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":"Sensors; Volume 20; Issue 18; Pages: 5212","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7570673","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7570673","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"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":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s20185212","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s20185212","pdf_url":"https://www.mdpi.com/1424-8220/20/18/5212/pdf?version=1600247647","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"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":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6600000262260437,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G7430910067","display_name":null,"funder_award_id":"NRF-2020R1F1A1060659","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3084484668.pdf","grobid_xml":"https://content.openalex.org/works/W3084484668.grobid-xml"},"referenced_works_count":66,"referenced_works":["https://openalex.org/W175750906","https://openalex.org/W1686810756","https://openalex.org/W1995562189","https://openalex.org/W2055911634","https://openalex.org/W2074788634","https://openalex.org/W2087618018","https://openalex.org/W2095705004","https://openalex.org/W2144005487","https://openalex.org/W2144354855","https://openalex.org/W2146334809","https://openalex.org/W2154579312","https://openalex.org/W2156338447","https://openalex.org/W2163605009","https://openalex.org/W2170240176","https://openalex.org/W2177486042","https://openalex.org/W2181741066","https://openalex.org/W2268875920","https://openalex.org/W2295001676","https://openalex.org/W2466877391","https://openalex.org/W2512885694","https://openalex.org/W2588353154","https://openalex.org/W2602034649","https://openalex.org/W2625297138","https://openalex.org/W2666547004","https://openalex.org/W2738561771","https://openalex.org/W2756275245","https://openalex.org/W2765815408","https://openalex.org/W2765860599","https://openalex.org/W2766272105","https://openalex.org/W2766756589","https://openalex.org/W2784665486","https://openalex.org/W2799149040","https://openalex.org/W2810418809","https://openalex.org/W2885005742","https://openalex.org/W2888786729","https://openalex.org/W2889717020","https://openalex.org/W2904753829","https://openalex.org/W2904938641","https://openalex.org/W2905361499","https://openalex.org/W2910444986","https://openalex.org/W2910655080","https://openalex.org/W2914913933","https://openalex.org/W2916370975","https://openalex.org/W2916979304","https://openalex.org/W2923473698","https://openalex.org/W2930753566","https://openalex.org/W2936113082","https://openalex.org/W2950518992","https://openalex.org/W2951123823","https://openalex.org/W2952665519","https://openalex.org/W2956824775","https://openalex.org/W2959133507","https://openalex.org/W2960746948","https://openalex.org/W2963929227","https://openalex.org/W2969889150","https://openalex.org/W2970737019","https://openalex.org/W2972724712","https://openalex.org/W2973037561","https://openalex.org/W2997700007","https://openalex.org/W2999309192","https://openalex.org/W3005716209","https://openalex.org/W3008039831","https://openalex.org/W3022013598","https://openalex.org/W3036062919","https://openalex.org/W6674330103","https://openalex.org/W6744544601"],"related_works":["https://openalex.org/W318616257","https://openalex.org/W3118254946","https://openalex.org/W2120267809","https://openalex.org/W2917043877","https://openalex.org/W4238520549","https://openalex.org/W3216173459","https://openalex.org/W2794357331","https://openalex.org/W4242611441","https://openalex.org/W4242034606","https://openalex.org/W2037174948"],"abstract_inverted_index":{"Artificial":[0],"intelligence":[1],"(AI)":[2],"and":[3,76,91,115,135,190,216,225,229],"machine":[4],"learning":[5],"(ML)":[6],"are":[7,50,97,106],"employed":[8],"to":[9,64,81,110,150,194],"make":[10],"systems":[11],"smarter.":[12],"Today,":[13],"the":[14,21,25,48,101,103,111,113,116,144,152,173,182,187,196,209,217,238,250],"speech":[15,30,59,188,220,223],"emotion":[16],"recognition":[17,33,138,231,247],"(SER)":[18],"system":[19,242],"evaluates":[20],"emotional":[22,211,219],"state":[23],"of":[24,73],"speaker":[26],"by":[27,53,156],"investigating":[28],"his/her":[29],"signal.":[31],"Emotion":[32],"is":[34,55,61],"a":[35,39,123,131,136,158,163,245],"challenging":[36],"task":[37],"for":[38,100,172],"machine.":[40],"In":[41,118],"addition,":[42],"making":[43],"it":[44,71,226],"smarter":[45],"so":[46],"that":[47,78,129,167,237],"emotions":[49],"efficiently":[51],"recognized":[52],"AI":[54],"equally":[56],"challenging.":[57],"The":[58,140,175,198,233],"signal":[60,67],"quite":[62],"hard":[63],"examine":[65],"using":[66,157],"processing":[68],"methods":[69],"because":[70],"consists":[72],"different":[74,95],"frequencies":[75],"features":[77,155,185],"vary":[79],"according":[80,109],"emotions,":[82,114],"such":[83],"as":[84],"anger,":[85],"fear,":[86],"sadness,":[87],"happiness,":[88],"boredom,":[89],"disgust,":[90],"surprise.":[92],"Even":[93],"though":[94],"algorithms":[96],"being":[98],"developed":[99],"SER,":[102],"success":[104],"rates":[105],"very":[107],"low":[108,132],"languages,":[112],"databases.":[117],"this":[119],"paper,":[120],"we":[121],"propose":[122],"new":[124],"lightweight":[125],"effective":[126],"SER":[127,200,241,252],"model":[128,178,201],"has":[130],"computational":[133],"complexity":[134],"high":[137],"accuracy.":[139],"suggested":[141],"method":[142],"uses":[143],"convolutional":[145],"neural":[146],"network":[147],"(CNN)":[148],"approach":[149],"learn":[151],"deep":[153],"frequency":[154,184],"plain":[159],"rectangular":[160],"filter":[161],"with":[162],"modified":[164],"pooling":[165],"strategy":[166],"have":[168],"more":[169],"discriminative":[170],"power":[171],"SER.":[174],"proposed":[176,199,239],"CNN":[177],"was":[179,191,202],"trained":[180],"on":[181],"extracted":[183],"from":[186],"data":[189],"then":[192],"tested":[193],"predict":[195],"emotions.":[197],"evaluated":[203],"over":[204],"two":[205],"benchmarks,":[206],"which":[207],"included":[208],"interactive":[210],"dyadic":[212],"motion":[213],"capture":[214],"(IEMOCAP)":[215],"berlin":[218],"database":[221],"(EMO-DB)":[222],"datasets,":[224],"obtained":[227],"77.01%":[228],"92.02%":[230],"results.":[232],"experimental":[234],"results":[235],"demonstrated":[236],"CNN-based":[240],"can":[243],"achieve":[244],"better":[246],"performance":[248],"than":[249],"state-of-the-art":[251],"systems.":[253]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":28},{"year":2024,"cited_by_count":34},{"year":2023,"cited_by_count":49},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":4}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}