{"id":"https://openalex.org/W7202035549","doi":"https://doi.org/10.59543/jidmis.v3.1409","title":"Pathological Voice Classification Using Empirical Mode Decomposition and Ensemble Empirical Mode Decomposition with Extreme Learning Machine","display_name":"Pathological Voice Classification Using Empirical Mode Decomposition and Ensemble Empirical Mode Decomposition with Extreme Learning Machine","publication_year":2026,"publication_date":"2026-08-08","ids":{"openalex":"https://openalex.org/W7202035549","doi":"https://doi.org/10.59543/jidmis.v3.1409"},"language":"en","primary_location":{"id":"doi:10.59543/jidmis.v3.1409","doi":"https://doi.org/10.59543/jidmis.v3.1409","is_oa":true,"landing_page_url":"https://doi.org/10.59543/jidmis.v3.1409","pdf_url":"https://jidmis.org/index.php/jidmis/article/download/1409/516","source":{"id":"https://openalex.org/S5407049300","display_name":"Journal of Intelligent Decision Making and Information Science","issn_l":"3079-0875","issn":["3079-0875"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Decision Making and Information Science","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://jidmis.org/index.php/jidmis/article/download/1409/516","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030334431","display_name":"Anil Kumar V","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I83737708","display_name":"REVA University","ror":"https://ror.org/03gtcxd54","country_code":"IN","type":"education","lineage":["https://openalex.org/I83737708"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Anil Kumar V","raw_affiliation_strings":["School of Electronics and Communication Engineering , REVA University , Bengaluru- 560064 , Karnataka , India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Communication Engineering , REVA University , Bengaluru- 560064 , Karnataka , India","institution_ids":["https://openalex.org/I83737708"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5030334431"],"corresponding_institution_ids":["https://openalex.org/I83737708"],"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":"3","issue":"6s","first_page":"464","last_page":"485"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10863","display_name":"Voice and Speech Disorders","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/3616","display_name":"Speech and Hearing"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10863","display_name":"Voice and Speech Disorders","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/3616","display_name":"Speech and Hearing"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.0017000000225380063,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.00039999998989515007,"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/pathological-voice-classification","display_name":"pathological voice classification","score":0.9919999837875366},{"id":"https://openalex.org/keywords/laryngeal-diseases","display_name":"laryngeal diseases","score":0.9459999799728394},{"id":"https://openalex.org/keywords/empirical-mode-decomposition","display_name":"empirical mode decomposition","score":0.7879999876022339},{"id":"https://openalex.org/keywords/ensemble-empirical-mode-decomposition","display_name":"ensemble empirical mode decomposition","score":1.0},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"extreme learning machine","score":0.9700000286102295},{"id":"https://openalex.org/keywords/intrinsic-mode-function","display_name":"intrinsic mode functions","score":0.7210000157356262},{"id":"https://openalex.org/keywords/hilbert-spectral-analysis","display_name":"Hilbert spectral analysis","score":0.921999990940094},{"id":"https://openalex.org/keywords/instantaneous-energy","display_name":"instantaneous energy","score":0.6679999828338623},{"id":"https://openalex.org/keywords/instantaneous-frequency","display_name":"instantaneous frequency","score":0.9739999771118164},{"id":"https://openalex.org/keywords/mode-mixing","display_name":"mode mixing","score":0.5419999957084656},{"id":"https://openalex.org/keywords/computer-aided-diagnosis","display_name":"computer-aided diagnosis","score":0.7319999933242798},{"id":"https://openalex.org/keywords/vocal-fold-vibration","display_name":"vocal fold vibration","score":0.6949999928474426}],"concepts":[{"id":"https://openalex.org/C25570617","wikidata":"https://www.wikidata.org/wiki/Q1006462","display_name":"Hilbert\u2013Huang transform","level":3,"score":0.9103000164031982},{"id":"https://openalex.org/C173988693","wikidata":"https://www.wikidata.org/wiki/Q678132","display_name":"Phonation","level":2,"score":0.736299991607666},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7196000218391418},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6165000200271606},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.6114000082015991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5942000150680542},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5708000063896179},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5299999713897705},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.517799973487854},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5152000188827515},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.45249998569488525},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4309999942779541},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4262999892234802},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4198000133037567},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4196999967098236},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.3970000147819519},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.35749998688697815},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.3402999937534332},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.31850001215934753},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.31679999828338623},{"id":"https://openalex.org/C2779581591","wikidata":"https://www.wikidata.org/wiki/Q36244","display_name":"Vowel","level":2,"score":0.30720001459121704},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2935999929904938},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.59543/jidmis.v3.1409","doi":"https://doi.org/10.59543/jidmis.v3.1409","is_oa":true,"landing_page_url":"https://doi.org/10.59543/jidmis.v3.1409","pdf_url":"https://jidmis.org/index.php/jidmis/article/download/1409/516","source":{"id":"https://openalex.org/S5407049300","display_name":"Journal of Intelligent Decision Making and Information Science","issn_l":"3079-0875","issn":["3079-0875"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Decision Making and Information Science","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.59543/jidmis.v3.1409","doi":"https://doi.org/10.59543/jidmis.v3.1409","is_oa":true,"landing_page_url":"https://doi.org/10.59543/jidmis.v3.1409","pdf_url":"https://jidmis.org/index.php/jidmis/article/download/1409/516","source":{"id":"https://openalex.org/S5407049300","display_name":"Journal of Intelligent Decision Making and Information Science","issn_l":"3079-0875","issn":["3079-0875"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent Decision Making and Information Science","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.5683000087738037,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7202035549.pdf","grobid_xml":"https://content.openalex.org/works/W7202035549.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2132842843","https://openalex.org/W4317436620","https://openalex.org/W4406049036","https://openalex.org/W4416046767","https://openalex.org/W2028602401","https://openalex.org/W2999456104","https://openalex.org/W7223463957","https://openalex.org/W70406107","https://openalex.org/W4415260885","https://openalex.org/W7001309085"],"abstract_inverted_index":{"Pathological":[0],"voice":[1],"analysis":[2,103],"has":[3],"been":[4],"proved":[5],"as":[6,153],"an":[7,125],"important":[8],"computer":[9],"aided":[10],"diagnostic":[11],"approach":[12],"for":[13],"early":[14],"identification":[15],"of":[16,31,81,113,197,204],"laryngeal":[17],"disorders":[18],"using":[19,124,148],"sustained":[20,77],"phonation":[21],"recordings.":[22],"Due":[23],"to":[24,39,44,71,131,169],"the":[25,82,170,193,212,216],"highly":[26],"non-linear":[27],"and":[28,65,96,104,110,115,138,158,174,202,208],"non-stationary":[29],"nature":[30],"speech":[32],"signals,":[33],"traditional":[34],"spectral":[35,102,111],"features":[36],"often":[37],"fail":[38],"capture":[40],"subtle":[41],"changes":[42],"related":[43],"pathological":[45,116],"vocal":[46],"fold":[47],"vibration.":[48],"In":[49],"this":[50],"paper,":[51],"we":[52],"propose":[53],"a":[54],"hybrid":[55,161],"feature":[56,120,163],"extraction":[57],"framework":[58,191],"by":[59,93],"combining":[60],"Empirical":[61,67],"Mode":[62,68],"Decomposition":[63,69],"(EMD)":[64],"Ensemble":[66],"(EEMD)":[70],"extract":[72],"discriminative":[73],"time-frequency":[74],"representations":[75],"from":[76,100],"vowel":[78],"(/a/)":[79],"recordings":[80],"VOICED":[83,213],"database.":[84],"The":[85,118,142,160,188],"decomposed":[86],"intrinsic":[87],"mode":[88],"functions":[89],"are":[90,122],"further":[91],"characterized":[92],"instantaneous":[94,97],"energy":[95],"frequency":[98],"obtained":[99,192],"Hilbert":[101],"statistical":[105],"descriptors":[106],"that":[107],"preserve":[108],"temporal":[109],"characteristics":[112],"healthy":[114],"voices.":[117],"resulting":[119],"vectors":[121],"classified":[123],"Extreme":[126],"Learning":[127],"Machine":[128],"(ELM)":[129],"due":[130],"its":[132],"fast":[133],"learning,":[134],"good":[135],"generalization":[136],"performance":[137,150,182],"low":[139],"computational":[140],"complexity.":[141],"experimental":[143,218],"evaluation":[144],"is":[145],"carried":[146],"out":[147],"standard":[149],"measures":[151],"such":[152],"accuracy,":[154],"sensitivity,":[155,199],"specificity,":[156,200],"precision":[157,201],"F1-score.":[159],"EMD\u2013EEMD":[162],"set":[164],"can":[165,175],"provide":[166],"complementary":[167],"information":[168],"individual":[171,185],"decomposition":[172,186],"methods":[173],"mitigate":[176],"mode-mixing":[177],"effects,":[178],"which":[179],"demonstrates":[180],"better":[181],"than":[183],"each":[184],"method.":[187],"proposed":[189],"EMD+EEMD-ELM":[190],"overall":[194],"classification":[195],"accuracy":[196],"98.74%,":[198],"F1-score":[203],"98.42%,":[205],"99.05%,":[206],"98.63%":[207],"98.52%":[209],"respectively":[210],"on":[211],"dataset":[214],"under":[215],"adopted":[217],"protocol.":[219]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-08-10T00:00:00"}
