{"id":"https://openalex.org/W4400646147","doi":"https://doi.org/10.1109/access.2024.3428336","title":"Triangular Region Cut-Mix Augmentation Algorithm-Based Speech Emotion Recognition System With Transfer Learning Approach","display_name":"Triangular Region Cut-Mix Augmentation Algorithm-Based Speech Emotion Recognition System With Transfer Learning Approach","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400646147","doi":"https://doi.org/10.1109/access.2024.3428336"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3428336","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3428336","pdf_url":null,"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":null,"license_id":null,"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://doi.org/10.1109/access.2024.3428336","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108902807","display_name":"V Preethi","orcid":null},"institutions":[{"id":"https://openalex.org/I145286018","display_name":"SRM Institute of Science and Technology","ror":"https://ror.org/050113w36","country_code":"IN","type":"education","lineage":["https://openalex.org/I145286018"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"V. Preethi","raw_affiliation_strings":["Department of Networking and Communications, School of Computing, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chennai, India"],"raw_orcid":"https://orcid.org/0000-0003-4055-5425","affiliations":[{"raw_affiliation_string":"Department of Networking and Communications, School of Computing, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chennai, India","institution_ids":["https://openalex.org/I145286018"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054601434","display_name":"V. Elizabeth Jesi","orcid":"https://orcid.org/0000-0001-7797-2586"},"institutions":[{"id":"https://openalex.org/I145286018","display_name":"SRM Institute of Science and Technology","ror":"https://ror.org/050113w36","country_code":"IN","type":"education","lineage":["https://openalex.org/I145286018"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"V. Elizabeth Jesi","raw_affiliation_strings":["Department of Networking and Communications, School of Computing, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Networking and Communications, School of Computing, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chennai, India","institution_ids":["https://openalex.org/I145286018"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5108902807"],"corresponding_institution_ids":["https://openalex.org/I145286018"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.6006,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.83493496,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"98436","last_page":"98449"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":1.0,"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"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9998000264167786,"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":0.9994999766349792,"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":0.8288636207580566},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.7344890832901001},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.583381175994873},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.48447442054748535},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.48176074028015137},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.45422035455703735},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4498502314090729},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4489631950855255},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3912276327610016}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8288636207580566},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.7344890832901001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.583381175994873},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.48447442054748535},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.48176074028015137},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.45422035455703735},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4498502314090729},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4489631950855255},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3912276327610016},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3428336","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3428336","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:287f2680af8b46d09f5d16a910268c43","is_oa":true,"landing_page_url":"https://doaj.org/article/287f2680af8b46d09f5d16a910268c43","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":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"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 12, Pp 98436-98449 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3428336","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3428336","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1599920681","https://openalex.org/W2063971957","https://openalex.org/W2099767163","https://openalex.org/W2125789230","https://openalex.org/W2194775991","https://openalex.org/W2526050071","https://openalex.org/W2619184049","https://openalex.org/W2746314669","https://openalex.org/W2752143737","https://openalex.org/W2765407302","https://openalex.org/W2885005742","https://openalex.org/W2899477876","https://openalex.org/W2903105043","https://openalex.org/W2936774411","https://openalex.org/W2963232380","https://openalex.org/W2963263347","https://openalex.org/W2963364041","https://openalex.org/W2963622428","https://openalex.org/W2964137095","https://openalex.org/W2970737019","https://openalex.org/W2972640480","https://openalex.org/W2973177780","https://openalex.org/W2992308087","https://openalex.org/W2997887270","https://openalex.org/W2998508940","https://openalex.org/W3010360545","https://openalex.org/W3022013598","https://openalex.org/W3023215041","https://openalex.org/W3035682985","https://openalex.org/W3047916742","https://openalex.org/W3084484668","https://openalex.org/W3089787895","https://openalex.org/W3094228441","https://openalex.org/W3096690837","https://openalex.org/W3099421655","https://openalex.org/W3106753828","https://openalex.org/W3107569919","https://openalex.org/W3114566572","https://openalex.org/W3126625480","https://openalex.org/W3134925817","https://openalex.org/W3158587543","https://openalex.org/W3161428216","https://openalex.org/W3163157357","https://openalex.org/W3173678936","https://openalex.org/W3177330184","https://openalex.org/W3207346153","https://openalex.org/W3213879871","https://openalex.org/W4288009632","https://openalex.org/W4293778726","https://openalex.org/W4295727797","https://openalex.org/W4364378283","https://openalex.org/W4372348599","https://openalex.org/W4389619460","https://openalex.org/W6636048551","https://openalex.org/W6726497184","https://openalex.org/W6738514645","https://openalex.org/W6743428213","https://openalex.org/W6751795773","https://openalex.org/W6762334975","https://openalex.org/W6765655789","https://openalex.org/W6765939562","https://openalex.org/W6771351431","https://openalex.org/W6776937213","https://openalex.org/W6783989761","https://openalex.org/W6794461119"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W4375868962","https://openalex.org/W2011227383","https://openalex.org/W2088854863","https://openalex.org/W3179495260","https://openalex.org/W1976719989","https://openalex.org/W3127543252","https://openalex.org/W2065606036","https://openalex.org/W2897924318","https://openalex.org/W2138997758"],"abstract_inverted_index":{"Recently,":[0],"spectrogram":[1],"energy":[2],"patterns":[3],"that":[4,62,155,273,296],"capture":[5],"emotional":[6],"information":[7,38,54,80,91],"have":[8,150],"demonstrated":[9],"strong":[10],"performance":[11,158],"in":[12,81,145,159,177,190,287,290,305],"the":[13,69,74,79,94,107,114,130,136,191,220,231,241,297,309],"vocal-based":[14],"image":[15,37,161,226,278],"emotion":[16,32,98,118,162,186],"detection":[17],"challenge.":[18],"The":[19,88,126],"proposed":[20,298],"augmentation":[21,168,238],"technique,":[22],"called":[23],"Triangular":[24],"Region":[25],"cut-mix,":[26],"is":[27,100,124,188],"a":[28,64,120,133,153,181,212,217,269,302],"novel":[29],"system":[30,299],"for":[31,184,277],"recognition.":[33],"It":[34],"utilizes":[35,58],"voice":[36,117,160],"to":[39,67,83,92,105,135,229,239,308],"enhance":[40,68,93,113],"classification":[41,227],"accuracy":[42,95,284,306],"by":[43],"focusing":[44],"on":[45],"triangular":[46,65,236,264],"regions":[47],"instead":[48],"of":[49,73,90,96,109,116,132,193,219,251,285],"box":[50],"regions,":[51],"while":[52,77,164],"minimizing":[53],"loss.":[55],"This":[56,172],"study":[57],"an":[59,247,283],"innovative":[60],"approach":[61],"incorporates":[63],"area":[66],"cutting":[70],"or":[71],"mixing":[72],"input":[75],"images,":[76],"preserving":[78],"order":[82,104],"create":[84],"additional":[85],"training":[86,110,243],"examples.":[87],"dearth":[89],"speech":[97,291],"recognition":[99,187],"therefore":[101],"mitigated.":[102],"In":[103,140],"increase":[106,304],"amount":[108],"data":[111,201,210],"and":[112,249],"precision":[115],"recognition,":[119],"vanilla":[121],"gradient":[122],"technique":[123],"employed.":[125],"pitch":[127],"attribution":[128],"demonstrates":[129,295],"significance":[131],"pixel":[134],"human":[137],"visual":[138],"system.":[139],"contrast,":[141],"transfer":[142],"learning":[143,257,262],"results":[144,294],"superior":[146],"performance.":[147],"Previous":[148],"studies":[149],"not":[151],"identified":[152],"model":[154,183,272,281,311],"achieves":[156,282],"good":[157],"identification":[163],"using":[165],"triangle":[166],"region":[167,237,265],"without":[169,258,312],"sacrificing":[170],"information.":[171],"limitation":[173],"has":[174,274,300],"been":[175],"observed":[176],"earlier":[178],"works.":[179],"Constructing":[180],"proficient":[182],"automatic":[185],"challenging":[189],"absence":[192],"annotated":[194],"data.":[195,244],"We":[196,223,245,267],"utilize":[197,268],"raw,":[198],"labeled":[199,242],"audio":[200,221],"from":[202],"kaggle\u2019s":[203],"Ravdess":[204],"dataset.":[205],"Initially,":[206],"we":[207,234],"convert":[208],"this":[209],"into":[211],"spectrogram,":[213],"which":[214],"serves":[215],"as":[216],"representation":[218],"image.":[222],"then":[224],"apply":[225],"algorithms":[228],"classify":[230],"emotion.":[232],"Additionally,":[233],"employ":[235],"expand":[240],"conduct":[246],"assessment":[248],"evaluation":[250],"two":[252],"distinct":[253],"methodologies:":[254],"1)":[255],"Transfer":[256,261],"augmentation;":[259],"2)":[260],"with":[263],"augmentation.":[266,313],"pre-trained":[270],"VGG16":[271],"undergone":[275],"pre-training":[276],"classification.":[279],"Our":[280],"84.2%":[286],"detecting":[288],"emotions":[289],"images.":[292],"Experimental":[293],"achieved":[301],"5.6%":[303],"compared":[307],"baseline":[310]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-10T08:33:47.465468","created_date":"2025-10-10T00:00:00"}