{"id":"https://openalex.org/W7204116002","doi":"https://doi.org/10.70917/ijcisim-2026-4998","title":"Intelligent Audio-based Emotion Recognition in Speech by Deep Learning and Feature Engineering Techniques","display_name":"Intelligent Audio-based Emotion Recognition in Speech by Deep Learning and Feature Engineering Techniques","publication_year":2026,"publication_date":"2026-08-23","ids":{"openalex":"https://openalex.org/W7204116002","doi":"https://doi.org/10.70917/ijcisim-2026-4998"},"language":"en","primary_location":{"id":"doi:10.70917/ijcisim-2026-4998","doi":"https://doi.org/10.70917/ijcisim-2026-4998","is_oa":true,"landing_page_url":"https://doi.org/10.70917/ijcisim-2026-4998","pdf_url":"https://cspub-ijcisim.org/index.php/ijcisim/article/download/4998/4120","source":{"id":"https://openalex.org/S5406979607","display_name":"International Journal of Computer Information Systems and Industrial Management Applications","issn_l":"2150-7988","issn":["2150-7988"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","poland-40","russia-white-list-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Information Systems and Industrial Management Applications","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W7204116002"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://cspub-ijcisim.org/index.php/ijcisim/article/download/4998/4120","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076500405","display_name":"G. Ramakrishna","orcid":"https://orcid.org/0000-0001-7213-5789","observed_orcids":["https://orcid.org/0000-0001-7213-5789"]},"institutions":[{"id":"https://openalex.org/I197081775","display_name":"Annamalai University","ror":"https://ror.org/01x24z140","country_code":"IN","type":"education","lineage":["https://openalex.org/I197081775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ramakrishna Gandi","raw_affiliation_strings":["Computer Science & Engineering, Faculty of Engineering & Technology, Annamalai University, Annamalainagar, Tamilnadu, INDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, Faculty of Engineering & Technology, Annamalai University, Annamalainagar, Tamilnadu, INDIA","institution_ids":["https://openalex.org/I197081775"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030956971","display_name":"A. Geetha","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I197081775","display_name":"Annamalai University","ror":"https://ror.org/01x24z140","country_code":"IN","type":"education","lineage":["https://openalex.org/I197081775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"A. Geetha","raw_affiliation_strings":["Computer Science & Engineering, Faculty of Engineering & Technology, Annamalai University, Annamalainagar, Tamilnadu, INDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, Faculty of Engineering & Technology, Annamalai University, Annamalainagar, Tamilnadu, INDIA","institution_ids":["https://openalex.org/I197081775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013607349","display_name":"B. Ramasubba Reddy","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405270480","display_name":"Mohan Babu University","ror":"https://ror.org/00s4s8963","country_code":"IN","type":"education","lineage":["https://openalex.org/I4405270480"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"B. Ramasubba Reddy","raw_affiliation_strings":["Department of Computer Science and Engineering, School of Computing, Mohan Babu University, Tirupati, Andhra Pradesh, INDIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, School of Computing, Mohan Babu University, Tirupati, Andhra Pradesh, INDIA","institution_ids":["https://openalex.org/I4405270480"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"19s","first_page":"14","last_page":"33"},"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/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"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":1.0,"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/T10201","display_name":"Speech Recognition and Synthesis","score":9.999999747378752e-05,"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/T10860","display_name":"Speech and Audio Processing","score":0.0,"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/speech-emotion-recognition","display_name":"speech emotion recognition","score":1.0},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"multilayer perceptron","score":0.8209999799728394},{"id":"https://openalex.org/keywords/mel-frequency-cepstral-coefficients","display_name":"Mel-frequency cepstral coefficients","score":0.8130000233650208},{"id":"https://openalex.org/keywords/spectral-contrast","display_name":"spectral contrast","score":0.9110000133514404},{"id":"https://openalex.org/keywords/pitch-features","display_name":"pitch features","score":0.9089999794960022},{"id":"https://openalex.org/keywords/prosodic-features","display_name":"prosodic features","score":0.9580000042915344},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"feature engineering","score":0.4880000054836273},{"id":"https://openalex.org/keywords/environmental-noise-robustness","display_name":"environmental noise robustness","score":0.6980000138282776},{"id":"https://openalex.org/keywords/speaker-variability","display_name":"speaker variability","score":0.8650000095367432},{"id":"https://openalex.org/keywords/cross-lingual-adaptation","display_name":"cross-lingual adaptation","score":0.9800000190734863},{"id":"https://openalex.org/keywords/six-basic-emotions","display_name":"six basic emotions","score":0.6949999928474426},{"id":"https://openalex.org/keywords/affective-computing","display_name":"affective computing","score":0.6150000095367432},{"id":"https://openalex.org/keywords/mental-health-monitoring","display_name":"mental health monitoring","score":0.8730000257492065},{"id":"https://openalex.org/keywords/human-computer-interaction","display_name":"human-computer interaction","score":0.9649999737739563}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7724000215530396},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7386000156402588},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.7235999703407288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6919999718666077},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6886000037193298},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5493999719619751},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.5364999771118164},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5164999961853027},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5088000297546387},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47999998927116394},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.44040000438690186},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4180000126361847},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4154999852180481},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.40540000796318054},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4011000096797943},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39149999618530273},{"id":"https://openalex.org/C6438553","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Affective computing","level":2,"score":0.3912999927997589},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.37389999628067017},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.37299999594688416},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.3716000020503998},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.361299991607666},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3190999925136566},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.28870001435279846},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.28349998593330383},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.27880001068115234},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2784000039100647},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2623000144958496},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.25369998812675476},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.70917/ijcisim-2026-4998","doi":"https://doi.org/10.70917/ijcisim-2026-4998","is_oa":true,"landing_page_url":"https://doi.org/10.70917/ijcisim-2026-4998","pdf_url":"https://cspub-ijcisim.org/index.php/ijcisim/article/download/4998/4120","source":{"id":"https://openalex.org/S5406979607","display_name":"International Journal of Computer Information Systems and Industrial Management Applications","issn_l":"2150-7988","issn":["2150-7988"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","poland-40","russia-white-list-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Information Systems and Industrial Management Applications","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.70917/ijcisim-2026-4998","doi":"https://doi.org/10.70917/ijcisim-2026-4998","is_oa":true,"landing_page_url":"https://doi.org/10.70917/ijcisim-2026-4998","pdf_url":"https://cspub-ijcisim.org/index.php/ijcisim/article/download/4998/4120","source":{"id":"https://openalex.org/S5406979607","display_name":"International Journal of Computer Information Systems and Industrial Management Applications","issn_l":"2150-7988","issn":["2150-7988"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","poland-40","russia-white-list-2"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Information Systems and Industrial Management Applications","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204116002.pdf","grobid_xml":"https://content.openalex.org/works/W7204116002.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W2030931454"],"related_works":["https://openalex.org/W7162004041","https://openalex.org/W7160835542","https://openalex.org/W7167097555","https://openalex.org/W4390237521","https://openalex.org/W2757184610","https://openalex.org/W7161110810","https://openalex.org/W4408963069","https://openalex.org/W7151901201","https://openalex.org/W3209219832","https://openalex.org/W7155520536"],"abstract_inverted_index":{"Speech":[0],"Emotion":[1],"Recognition":[2],"(SER)":[3],"is":[4,202],"now":[5],"progressively":[6],"vital":[7],"for":[8,23,206,230],"many":[9,191],"practical":[10],"uses":[11],"including":[12],"virtual":[13],"assistants,":[14],"customer":[15],"service,":[16],"and":[17,33,40,73,83,88,106,120,184,227,252,272,276],"healthcare":[18],"monitoring":[19,251],"as":[20,22],"well":[21],"SER":[24,59,168],"systems":[25],"still":[26],"suffer":[27],"with":[28,149,162],"environmental":[29],"noise,":[30],"speaker":[31],"variability,":[32],"cross-lingual":[34,277],"adaptation":[35,278],"that":[36],"affect":[37],"their":[38],"accuracy":[39,124,148],"generalizing":[41],"power":[42,183],"even":[43],"if":[44],"they":[45],"have":[46],"made":[47],"tremendous":[48],"progress.":[49],"This":[50,218],"work":[51,153,219],"introduces":[52],"ExpressNet,":[53],"an":[54],"optimum":[55],"Multi-Layer":[56],"Perceptron":[57],"(MLP)-based":[58],"model":[60,95,189],"aimed":[61],"to":[62,96,144,166,180,248],"solve":[63],"these":[64],"issues":[65],"by":[66,223],"leveraging":[67],"a":[68,89,109,122,173,203,214,225],"wide":[69],"range":[70],"of":[71,125,130,157,187,244],"prosodic":[72],"spectral":[74,81],"qualities":[75],"incorporating":[76],"Mel-Frequency":[77],"Cepstral":[78],"Coefficients":[79],"(MFCCs),":[80],"contrast,":[82],"pitch":[84],"variations.":[85],"ReLU":[86],"activation":[87],"softmax":[90],"output":[91],"layer":[92],"allow":[93],"the":[94,117,128,139,155,182,188,281],"classify":[97],"six":[98],"emotional":[99,221,238,262],"states:":[100],"anger,":[101],"disgust,":[102],"fear,":[103],"happiness,":[104],"neutral,":[105],"sad":[107],"using":[108,116],"deep":[110,159],"learning":[111,160,271],"architecture.":[112],"We":[113],"assess":[114],"ExpressNet":[115,201],"CREMA-D":[118],"dataset":[119],"achieve":[121],"test":[123],"92.97%,":[126],"above":[127],"results":[129],"previous":[131],"state-of-the-art":[132],"approaches.":[133],"Particularly":[134],"real-time":[135],"applications":[136],"gain":[137],"from":[138,195],"method":[140],"since":[141,211],"it":[142,212,256],"helps":[143],"blend":[145],"high":[146],"classification":[147],"computing":[150,222],"efficiency.":[151],"Our":[152],"emphasizes":[154],"need":[156],"applying":[158],"methods":[161],"enhanced":[163],"feature":[164],"engineering":[165],"improve":[167,280],"performance.":[169],"Furthermore,":[170],"we":[171],"show":[172,181],"thorough":[174],"assessment":[175],"over":[176],"numerous":[177],"benchmark":[178],"datasets":[179],"applicability":[185],"capacity":[186],"in":[190,208,237,264],"different":[192],"settings.":[193],"Apart":[194],"being":[196],"better":[197],"than":[198],"other":[199],"options,":[200],"consistent":[204],"choice":[205],"use":[207],"real-world":[209],"settings":[210],"has":[213],"low":[215],"overfitting":[216],"rate.":[217],"advances":[220],"providing":[224],"solid":[226],"scalable":[228],"foundation":[229],"SER,":[231],"which":[232],"will":[233,279],"enable":[234],"further":[235],"research":[236,268],"recognition":[239],"systems.":[240],"The":[241],"probable":[242],"utilization":[243],"this":[245],"technique":[246],"extends":[247],"mental":[249],"health":[250],"human-computer":[253],"interaction":[254],"because":[255],"demonstrates":[257],"excellence":[258],"at":[259],"handling":[260],"complex":[261],"patterns":[263],"voice":[265],"signals.":[266],"Extensive":[267],"into":[269],"self-supervised":[270],"multimodal":[273],"data":[274],"integration":[275],"model's":[282],"potential":[283],"across":[284],"multiple":[285],"application":[286],"scenarios.":[287]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-08-25T00:00:00"}