{"id":"https://openalex.org/W4399374391","doi":"https://doi.org/10.1109/icit58233.2024.10540745","title":"Enhancing Speech Emotion Recognition in Urdu Using Bi-GRU Networks: An In-Depth Analysis of Acoustic Features and Model Interpretability","display_name":"Enhancing Speech Emotion Recognition in Urdu Using Bi-GRU Networks: An In-Depth Analysis of Acoustic Features and Model Interpretability","publication_year":2024,"publication_date":"2024-03-25","ids":{"openalex":"https://openalex.org/W4399374391","doi":"https://doi.org/10.1109/icit58233.2024.10540745"},"language":"en","primary_location":{"id":"doi:10.1109/icit58233.2024.10540745","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icit58233.2024.10540745","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Industrial Technology (ICIT)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016156963","display_name":"Muhammad Adeel","orcid":"https://orcid.org/0000-0001-7021-8812"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Muhammad Adeel","raw_affiliation_strings":["Guilin University of Electronic Technology,Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education,Guilin,People's Republic of China,541004","Academy of Marine Information Technology, Guilin University of Electronic Technology, Beihai, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology,Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education,Guilin,People's Republic of China,541004","institution_ids":["https://openalex.org/I5343935"]},{"raw_affiliation_string":"Academy of Marine Information Technology, Guilin University of Electronic Technology, Beihai, People's Republic of China","institution_ids":["https://openalex.org/I5343935"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037894772","display_name":"Zhi-Yong Tao","orcid":"https://orcid.org/0000-0003-4732-5059"},"institutions":[{"id":"https://openalex.org/I5343935","display_name":"Guilin University of Electronic Technology","ror":"https://ror.org/05arjae42","country_code":"CN","type":"education","lineage":["https://openalex.org/I5343935"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi-Yong Tao","raw_affiliation_strings":["Guilin University of Electronic Technology,Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education,Guilin,People's Republic of China,541004","Academy of Marine Information Technology, Guilin University of Electronic Technology, Beihai, People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guilin University of Electronic Technology,Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education,Guilin,People's Republic of China,541004","institution_ids":["https://openalex.org/I5343935"]},{"raw_affiliation_string":"Academy of Marine Information Technology, Guilin University of Electronic Technology, Beihai, People's Republic of China","institution_ids":["https://openalex.org/I5343935"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I5343935"],"apc_list":null,"apc_paid":null,"fwci":5.8411,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.96153033,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9990000128746033,"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":0.9987999796867371,"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/computer-science","display_name":"Computer science","score":0.7662665843963623},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6680426597595215},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.585638165473938},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5536914467811584},{"id":"https://openalex.org/keywords/urdu","display_name":"Urdu","score":0.5196422338485718},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4459708333015442},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.42987900972366333},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41829681396484375},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3614305853843689}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7662665843963623},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6680426597595215},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.585638165473938},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5536914467811584},{"id":"https://openalex.org/C2777350258","wikidata":"https://www.wikidata.org/wiki/Q1617","display_name":"Urdu","level":2,"score":0.5196422338485718},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4459708333015442},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.42987900972366333},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41829681396484375},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3614305853843689},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icit58233.2024.10540745","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icit58233.2024.10540745","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Industrial Technology (ICIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2239141610","https://openalex.org/W2905903577","https://openalex.org/W3023491306","https://openalex.org/W3162343586","https://openalex.org/W4221122497","https://openalex.org/W4221139382","https://openalex.org/W4283711157","https://openalex.org/W4311970277","https://openalex.org/W4315490759","https://openalex.org/W4321496488","https://openalex.org/W4323665375","https://openalex.org/W4367677024","https://openalex.org/W4377819254","https://openalex.org/W4388470286","https://openalex.org/W4389252851"],"related_works":["https://openalex.org/W2736574136","https://openalex.org/W2038216521","https://openalex.org/W4399693842","https://openalex.org/W2399955410","https://openalex.org/W3126677997","https://openalex.org/W2565286512","https://openalex.org/W2097377227","https://openalex.org/W2933782699","https://openalex.org/W4317383455","https://openalex.org/W2565238693"],"abstract_inverted_index":{"This":[0,144,188],"paper":[1,189],"introduces":[2],"an":[3],"innovative":[4],"approach":[5],"to":[6,112],"Speech":[7],"Emotion":[8],"Recognition":[9],"(SER)":[10],"for":[11,81,197,206],"Pakistani":[12],"Urdu,":[13,201],"employing":[14],"the":[15,36,61,107,147,160,183,192],"URDU":[16,161],"dataset,":[17,48],"a":[18,126,203],"specialized":[19],"resource":[20],"in":[21,119,134,152,155,212],"this":[22,47,120],"domain,":[23],"and":[24,39,60,76,142,176,186,209],"utilizing":[25],"Bidirectional":[26],"Gated":[27],"Recurrent":[28],"Unit":[29],"(Bi-GRU)":[30],"networks.":[31],"Our":[32,69],"study":[33,121],"concentrates":[34],"on":[35,92],"meticulous":[37],"extraction":[38],"thorough":[40],"analysis":[41],"of":[42,88,109,130,149,194],"crucial":[43],"acoustic":[44],"features":[45,111],"from":[46],"including":[49],"Mel":[50],"Frequency":[51,56],"Cepstral":[52,57],"Coefficients":[53,58],"(MFCCs),":[54],"Gam-matone":[55],"(GFCCs),":[59],"ex-tended":[62],"Geneva":[63],"Minimalistic":[64],"Acoustic":[65],"Parameter":[66],"Set":[67],"(eGeMAPS).":[68],"methodology":[70],"integrates":[71],"sophisticated":[72],"feature":[73],"engineering,":[74],"normalization,":[75],"deploying":[77],"advanced":[78],"Bi-GRU":[79,116,150],"architectures":[80],"deep":[82],"learning":[83],"models.":[84],"A":[85],"significant":[86],"focus":[87],"our":[89,164],"work":[90,165],"is":[91],"model":[93,117],"interpretability,":[94],"achieved":[95],"through":[96,169],"SHAP":[97],"(SHapley":[98],"Additive":[99],"exPlanations)":[100],"analysis,":[101,173],"which":[102],"provides":[103],"valuable":[104],"insights":[105],"into":[106],"contributions":[108],"different":[110],"emotion":[113],"recognition.":[114],"The":[115],"developed":[118],"demonstrates":[122],"exceptional":[123],"proficiency,":[124],"achieving":[125],"peak":[127],"validation":[128,168],"accuracy":[129],"approximately":[131],"91":[132],"%":[133],"identifying":[135],"emotions":[136],"such":[137],"as":[138],"sadness,":[139],"neutrality,":[140],"happiness,":[141],"anger.":[143],"research":[145,208],"underscores":[146],"effectiveness":[148],"networks":[151],"SER,":[153,195],"particularly":[154],"Urdu":[156],"language":[157],"processing,":[158],"using":[159],"dataset.":[162],"Additionally,":[163],"includes":[166],"comprehensive":[167],"visualization":[170],"techniques,":[171],"error":[172],"confusion":[174],"matrices,":[175],"Receiver":[177],"Operating":[178],"Characteristic":[179],"(ROC)":[180],"curves,":[181],"reinforcing":[182],"model's":[184],"robustness":[185],"reliability.":[187],"significantly":[190],"advances":[191],"field":[193],"especially":[196],"low-resource":[198],"languages":[199],"like":[200],"offering":[202],"foundational":[204],"framework":[205],"future":[207],"practical":[210],"applications":[211],"emotionally":[213],"intelligent":[214],"human-computer":[215],"interaction.":[216]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}