{"id":"https://openalex.org/W4402260579","doi":"https://doi.org/10.1109/access.2024.3454825","title":"Improved Laryngeal Pathology Detection Based on Bottleneck Convolutional Networks and MFCC","display_name":"Improved Laryngeal Pathology Detection Based on Bottleneck Convolutional Networks and MFCC","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4402260579","doi":"https://doi.org/10.1109/access.2024.3454825"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3454825","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3454825","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.2024.3454825","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036297003","display_name":"Mohamed Cherif Amara Korba","orcid":"https://orcid.org/0000-0003-3888-8765"},"institutions":[{"id":"https://openalex.org/I1288970718","display_name":"Mohamed-Cherif Messaadia University","ror":"https://ror.org/04pn9tn44","country_code":"DZ","type":"education","lineage":["https://openalex.org/I1288970718"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Mohamed Cherif Amara Korba","raw_affiliation_strings":["LEER Laboratory, Mohamed Cherif Messaadia University-Souk Ahras, Souk Ahras, Algeria"],"raw_orcid":"https://orcid.org/0000-0003-3888-8765","affiliations":[{"raw_affiliation_string":"LEER Laboratory, Mohamed Cherif Messaadia University-Souk Ahras, Souk Ahras, Algeria","institution_ids":["https://openalex.org/I1288970718"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090701248","display_name":"Hakim Doghmane","orcid":"https://orcid.org/0000-0002-1425-3071"},"institutions":[{"id":"https://openalex.org/I4210097536","display_name":"University of Guelma","ror":"https://ror.org/00xe6p546","country_code":"DZ","type":"education","lineage":["https://openalex.org/I4210097536"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Hakim Doghmane","raw_affiliation_strings":["PI:MIS Laboratory, Universite 8 Mai 1945 Guelma, Guelma, Algeria"],"raw_orcid":"https://orcid.org/0000-0002-1425-3071","affiliations":[{"raw_affiliation_string":"PI:MIS Laboratory, Universite 8 Mai 1945 Guelma, Guelma, Algeria","institution_ids":["https://openalex.org/I4210097536"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028412075","display_name":"Khaled Khelil","orcid":"https://orcid.org/0000-0001-7237-2725"},"institutions":[{"id":"https://openalex.org/I1288970718","display_name":"Mohamed-Cherif Messaadia University","ror":"https://ror.org/04pn9tn44","country_code":"DZ","type":"education","lineage":["https://openalex.org/I1288970718"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Khaled Khelil","raw_affiliation_strings":["LEER Laboratory, Mohamed Cherif Messaadia University-Souk Ahras, Souk Ahras, Algeria"],"raw_orcid":"https://orcid.org/0000-0001-7237-2725","affiliations":[{"raw_affiliation_string":"LEER Laboratory, Mohamed Cherif Messaadia University-Souk Ahras, Souk Ahras, Algeria","institution_ids":["https://openalex.org/I1288970718"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059545224","display_name":"Kamel Messaoudi","orcid":"https://orcid.org/0000-0002-0985-9095"},"institutions":[{"id":"https://openalex.org/I1288970718","display_name":"Mohamed-Cherif Messaadia University","ror":"https://ror.org/04pn9tn44","country_code":"DZ","type":"education","lineage":["https://openalex.org/I1288970718"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Kamel Messaoudi","raw_affiliation_strings":["LEER Laboratory, Mohamed Cherif Messaadia University-Souk Ahras, Souk Ahras, Algeria"],"raw_orcid":"https://orcid.org/0000-0002-0985-9095","affiliations":[{"raw_affiliation_string":"LEER Laboratory, Mohamed Cherif Messaadia University-Souk Ahras, Souk Ahras, Algeria","institution_ids":["https://openalex.org/I1288970718"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.3218,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.88970588,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"12","issue":null,"first_page":"124801","last_page":"124815"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10863","display_name":"Voice and Speech Disorders","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10863","display_name":"Voice and Speech Disorders","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9768999814987183,"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":0.9757000207901001,"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":0.7594108581542969},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.7540090084075928},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.5121192932128906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38627997040748596},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3464391827583313},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.261405885219574},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.061080873012542725}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7594108581542969},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.7540090084075928},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.5121192932128906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38627997040748596},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3464391827583313},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.261405885219574},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.061080873012542725}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3454825","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3454825","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:b646881b9b674643a43963c30d865f29","is_oa":true,"landing_page_url":"https://doaj.org/article/b646881b9b674643a43963c30d865f29","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 124801-124815 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3454825","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3454825","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":[{"score":0.44999998807907104,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W78415016","https://openalex.org/W254692632","https://openalex.org/W1498180239","https://openalex.org/W1558049005","https://openalex.org/W1964000773","https://openalex.org/W1972191071","https://openalex.org/W1995562189","https://openalex.org/W2013459182","https://openalex.org/W2016125416","https://openalex.org/W2016730668","https://openalex.org/W2021320575","https://openalex.org/W2023238506","https://openalex.org/W2024904926","https://openalex.org/W2039435081","https://openalex.org/W2044406255","https://openalex.org/W2046678753","https://openalex.org/W2092514808","https://openalex.org/W2094008917","https://openalex.org/W2100971813","https://openalex.org/W2101895618","https://openalex.org/W2112844139","https://openalex.org/W2117095944","https://openalex.org/W2123608681","https://openalex.org/W2125042854","https://openalex.org/W2132025473","https://openalex.org/W2155295839","https://openalex.org/W2157630368","https://openalex.org/W2158698691","https://openalex.org/W2171630550","https://openalex.org/W2217954322","https://openalex.org/W2296708431","https://openalex.org/W2321038435","https://openalex.org/W2326988116","https://openalex.org/W2344936922","https://openalex.org/W2516286059","https://openalex.org/W2762852562","https://openalex.org/W2775461895","https://openalex.org/W2783316790","https://openalex.org/W2804259516","https://openalex.org/W2896464508","https://openalex.org/W2897150037","https://openalex.org/W2898186885","https://openalex.org/W2945533554","https://openalex.org/W2959813266","https://openalex.org/W2962949934","https://openalex.org/W3014647115","https://openalex.org/W3015897612","https://openalex.org/W3016093409","https://openalex.org/W3041208418","https://openalex.org/W3125384922","https://openalex.org/W3152745858","https://openalex.org/W3161839447","https://openalex.org/W3204774355","https://openalex.org/W3209383001","https://openalex.org/W3211925797","https://openalex.org/W4200159303","https://openalex.org/W4297841902","https://openalex.org/W4372334073","https://openalex.org/W4372338343","https://openalex.org/W4378715586","https://openalex.org/W4385728310","https://openalex.org/W4387672817","https://openalex.org/W4388170825","https://openalex.org/W4389036626","https://openalex.org/W4390007540","https://openalex.org/W4391669270","https://openalex.org/W4392943712","https://openalex.org/W4396508758","https://openalex.org/W6746932923"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Automatic":[0],"detection":[1,17,52,66,166],"of":[2,15,38,122,133,173,192,207,212],"laryngeal":[3],"disorders":[4],"via":[5],"voice":[6,50],"analysis":[7],"allows":[8],"for":[9,188],"early":[10],"diagnosis.":[11],"However,":[12],"the":[13,35,95,103,119,123,174,189,193],"effectiveness":[14],"AI-based":[16,60],"methods":[18],"is":[19,55,113,138,186],"often":[20],"limited,":[21],"mainly":[22],"due":[23],"to":[24,29,64,94,102],"insufficient":[25],"training":[26],"data":[27],"subject":[28],"confidentiality":[30],"constraints,":[31],"as":[32,34,91],"well":[33],"wide":[36],"range":[37],"pathologies,":[39],"which":[40,130,177],"hinders":[41],"accurate":[42],"detection.":[43],"To":[44],"address":[45],"these":[46],"issues,":[47],"an":[48,58,210],"automatic":[49],"disorder":[51],"(AVDD)":[53],"system":[54],"proposed,":[56],"employing":[57],"innovative":[59],"feature":[61,88,198],"extraction":[62],"approach":[63,112],"improve":[65],"performance.":[67],"The":[68,110,136,156,196],"approach,":[69],"termed":[70],"MFCC-CBN,":[71],"employs":[72],"Mel-frequency":[73],"cepstral":[74],"coefficients":[75],"(MFCC)":[76],"with":[77],"a":[78,86,164,204],"convolutional":[79],"bottleneck":[80],"network":[81],"(CBN).":[82],"It":[83],"also":[84],"integrates":[85],"diverse":[87],"set,":[89],"such":[90],"measurements":[92],"related":[93],"fundamental":[96],"frequency":[97],"(F0)":[98],"perturbation,":[99],"features":[100],"specific":[101],"glottal":[104],"source,":[105],"and":[106,151,168,209],"conventional":[107],"MFCC":[108],"features.":[109],"proposed":[111],"validated":[114],"through":[115],"comprehensive":[116],"experiments":[117],"on":[118],"public":[120],"database":[121],"Pr\u00edncipe":[124],"de":[125],"Asturias":[126],"University":[127],"Hospital":[128],"(HUPA),":[129],"contains":[131],"recordings":[132],"sustained":[134],"vowels.":[135],"method":[137,162],"tested":[139],"using":[140],"various":[141],"classifiers,":[142],"including":[143],"Support":[144],"Vector":[145],"Machine":[146],"(SVM),":[147],"Random":[148],"Forest":[149],"(RF),":[150],"eXtreme":[152],"Gradient":[153],"Boosting":[154],"(XGBoost).":[155],"obtained":[157],"results":[158],"show":[159],"that":[160],"our":[161],"provides":[163],"high":[165],"rate":[167],"maintains":[169],"stable":[170],"performance":[171,190],"regardless":[172],"classifier":[175],"used,":[176],"reveals":[178],"its":[179],"good":[180],"generalization.":[181],"A":[182],"5-fold":[183],"cross-validation":[184],"technique":[185],"adopted":[187],"evaluation":[191],"AVDD":[194],"system.":[195],"optimal":[197],"configuration":[199],"surpasses":[200],"state-of-the-art":[201],"results,":[202],"achieving":[203],"classification":[205],"accuracy":[206],"88.79%":[208],"F1-score":[211],"0.88.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}