{"id":"https://openalex.org/W7162489785","doi":"https://doi.org/10.1109/access.2026.3697537","title":"Complementary Standard and Inverted Power Normalized Gammachirp Cepstral Approach for Noise-Robust Speaker Identification","display_name":"Complementary Standard and Inverted Power Normalized Gammachirp Cepstral Approach for Noise-Robust Speaker Identification","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7162489785","doi":"https://doi.org/10.1109/access.2026.3697537"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3697537","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3697537","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2026.3697537","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090043599","display_name":"Youssef Zouhir","orcid":null},"institutions":[{"id":"https://openalex.org/I179097149","display_name":"University of Carthage","ror":"https://ror.org/057x6za15","country_code":"TN","type":"education","lineage":["https://openalex.org/I179097149"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Youssef Zouhir","raw_affiliation_strings":["Research Laboratory Smart Electricity & ICT (SE&ICT Lab), LR18ES44, National Engineering School of Carthage, University of Carthage, Tunis, Tunisia"],"raw_orcid":"https://orcid.org/0000-0001-7227-1297","affiliations":[{"raw_affiliation_string":"Research Laboratory Smart Electricity & ICT (SE&ICT Lab), LR18ES44, National Engineering School of Carthage, University of Carthage, Tunis, Tunisia","institution_ids":["https://openalex.org/I179097149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023188674","display_name":"Mohamed Zarka","orcid":"https://orcid.org/0000-0003-2624-0400"},"institutions":[{"id":"https://openalex.org/I179097149","display_name":"University of Carthage","ror":"https://ror.org/057x6za15","country_code":"TN","type":"education","lineage":["https://openalex.org/I179097149"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Mohamed Zarka","raw_affiliation_strings":["Research Laboratory Smart Electricity & ICT (SE&ICT Lab), LR18ES44, National Engineering School of Carthage, University of Carthage, Tunis, Tunisia"],"raw_orcid":"https://orcid.org/0000-0003-2624-0400","affiliations":[{"raw_affiliation_string":"Research Laboratory Smart Electricity & ICT (SE&ICT Lab), LR18ES44, National Engineering School of Carthage, University of Carthage, Tunis, Tunisia","institution_ids":["https://openalex.org/I179097149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073965040","display_name":"Lilia El Amraoui","orcid":"https://orcid.org/0000-0002-0581-798X"},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Lilia El Amraoui","raw_affiliation_strings":["Department of Electrical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-0581-798X","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, College of Engineering, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087211163","display_name":"Ka\u00efs Ouni","orcid":"https://orcid.org/0000-0003-1989-5177"},"institutions":[{"id":"https://openalex.org/I179097149","display_name":"University of Carthage","ror":"https://ror.org/057x6za15","country_code":"TN","type":"education","lineage":["https://openalex.org/I179097149"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Kais Ouni","raw_affiliation_strings":["Research Laboratory Smart Electricity & ICT (SE&ICT Lab), LR18ES44, National Engineering School of Carthage, University of Carthage, Tunis, Tunisia"],"raw_orcid":"https://orcid.org/0000-0003-1989-5177","affiliations":[{"raw_affiliation_string":"Research Laboratory Smart Electricity & ICT (SE&ICT Lab), LR18ES44, National Engineering School of Carthage, University of Carthage, Tunis, Tunisia","institution_ids":["https://openalex.org/I179097149"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.62330237,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"84564","last_page":"84585"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.5546000003814697,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.5546000003814697,"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":0.22259999811649323,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.022600000724196434,"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/speaker-identification","display_name":"Speaker identification","score":0.7451000213623047},{"id":"https://openalex.org/keywords/cepstrum","display_name":"Cepstrum","score":0.6794000267982483},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.5676000118255615},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.5180000066757202},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4702000021934509},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4433000087738037},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4413999915122986}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8032000064849854},{"id":"https://openalex.org/C2986627078","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker identification","level":3,"score":0.7451000213623047},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7069000005722046},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.6794000267982483},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.5676000118255615},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.5180000066757202},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4702000021934509},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4690999984741211},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4433000087738037},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4413999915122986},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C2982762665","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker verification","level":3,"score":0.27079999446868896},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2680000066757202},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2655999958515167},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2590000033378601}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3697537","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3697537","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a077799c51014d26883826316959266c","is_oa":true,"landing_page_url":"https://doaj.org/article/a077799c51014d26883826316959266c","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 14, Pp 84564-84585 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3697537","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3697537","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3761647907","display_name":null,"funder_award_id":"PNURSP2026R831","funder_id":"https://openalex.org/F4320322484","funder_display_name":"Princess Nourah Bint Abdulrahman University"}],"funders":[{"id":"https://openalex.org/F4320322484","display_name":"Princess Nourah Bint Abdulrahman University","ror":"https://ror.org/05b0cyh02"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Despite":[0],"the":[1,42,104,107,121,131,190],"natural":[2],"ability":[3],"of":[4,106,164,192],"humans":[5],"to":[6,48,76,112,173],"recognize":[7],"speakers":[8],"in":[9,46,53,154,220],"noisy":[10],"environments,":[11],"automatic":[12],"speaker":[13,50,150,199],"recognition":[14,51,162],"systems":[15,218],"still":[16],"face":[17],"significant":[18],"performance":[19],"decrease":[20],"under":[21],"such":[22],"conditions.":[23,223],"This":[24],"paper":[25],"introduces":[26],"a":[27,114,208],"complementary":[28],"feature":[29,206],"extraction":[30],"approach":[31,58],"that":[32,130,204],"concatenates":[33],"the\u201cinverted":[34],"Power":[35],"Normalized":[36],"Gammachirp":[37,65],"Cepstral\u201d":[38],"(invPNGC)":[39],"coefficients":[40,45,109],"with":[41,125],"original":[43],"PNGC":[44,158],"order":[47],"enhance":[49],"robustness":[52],"challenging":[54,221],"acoustic":[55],"environments.":[56],"TheinvPNGC":[57],"integrates":[59],"two":[60,108],"key":[61],"innovations:":[62],"(1)":[63],"an\u201cInverted":[64],"FilterBank\u201d":[66],"(invGcFB)":[67],"using":[68],"an\u201cinverted":[69],"Equivalent":[70],"Rectangular":[71],"Bandwidth\u201d":[72],"(invERB)":[73],"rate":[74],"scale":[75],"provide":[77],"high":[78,81],"resolution":[79],"at":[80],"frequencies,":[82],"effectively":[83],"capturing":[84],"speaker-specific":[85],"consonantal":[86],"information":[87],"often":[88],"de-emphasized":[89],"by":[90,99],"traditional":[91],"methods,":[92],"and":[93,142,157,167,183,214],"(2)":[94],"a\u201cNoise":[95],"Suppression":[96],"Module\u201d(NSM)":[97],"inspired":[98],"human":[100],"auditory":[101],"masking.":[102],"Furthermore,":[103],"concatenation":[105],"yields":[110],"thecmpPNGC":[111,205],"capture":[113],"comprehensive":[115],"spectral":[116,195],"representation.":[117],"Comprehensive":[118],"experiments":[119],"on":[120],"TIMIT":[122],"database":[123],"mixed":[124],"AURORA":[126],"noise":[127,222],"types":[128],"demonstrate":[129],"proposed":[132],"method":[133],"significantly":[134],"outperforms":[135],"baseline":[136],"techniques":[137],"(PNGC,":[138],"PNCC,":[139,176],"MFCC,":[140,179],"FDLP,":[141,182],"FDLP-Mel)":[143],"using\u201cGaussian":[144],"Mixture":[145],"Model-Universal":[146],"Background":[147],"Model\u201d(GMM-UBM)":[148],"for":[149,175,178,181,185,197,211],"modeling.":[151],"For":[152],"instance,":[153],"Exhibition":[155],"noise,cmpPNGC,invPNGC":[156],"achieved":[159],"an":[160],"average":[161],"accuracy":[163],"77.38%,":[165],"73.87%":[166],"66.75%":[168],"(0-30dB":[169],"SNR)":[170],"respectively,":[171],"compared":[172],"50.35%":[174],"48.43%":[177],"49.96%":[180],"36.45%":[184],"FDLP-Mel.":[186],"These":[187,201],"results":[188],"confirm":[189],"efficacy":[191],"prioritizing":[193],"high-frequency":[194],"cues":[196],"robust":[198],"identification.":[200],"findings":[202],"suggest":[203],"offers":[207],"reliable":[209],"solution":[210],"biometric":[212],"authentication":[213],"forensic":[215],"voice":[216],"analysis":[217],"deployed":[219]},"counts_by_year":[],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2026-05-28T00:00:00"}