{"id":"https://openalex.org/W2618430901","doi":"https://doi.org/10.1109/iwbf.2017.7935102","title":"Speaker identification evaluation based on the speech biometric and i-vector model using the TIMIT and NTIMIT databases","display_name":"Speaker identification evaluation based on the speech biometric and i-vector model using the TIMIT and NTIMIT databases","publication_year":2017,"publication_date":"2017-04-01","ids":{"openalex":"https://openalex.org/W2618430901","doi":"https://doi.org/10.1109/iwbf.2017.7935102","mag":"2618430901"},"language":"en","primary_location":{"id":"doi:10.1109/iwbf.2017.7935102","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwbf.2017.7935102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 5th International Workshop on Biometrics and Forensics (IWBF)","raw_type":"proceedings-article"},"type":"article","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/A5053424993","display_name":"Musab T. S. Al-Kaltakchi","orcid":"https://orcid.org/0000-0001-5542-9144"},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Musab T. S. Al-Kaltakchi","raw_affiliation_strings":["Newcastle University, Newcastle upon Tyne, Tyne and Wear, GB"],"affiliations":[{"raw_affiliation_string":"Newcastle University, Newcastle upon Tyne, Tyne and Wear, GB","institution_ids":["https://openalex.org/I84884186"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084431277","display_name":"Wai Lok Woo","orcid":"https://orcid.org/0000-0002-8698-7605"},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wai L. Woo","raw_affiliation_strings":["Newcastle University, Newcastle upon Tyne, Tyne and Wear, GB"],"affiliations":[{"raw_affiliation_string":"Newcastle University, Newcastle upon Tyne, Tyne and Wear, GB","institution_ids":["https://openalex.org/I84884186"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111469348","display_name":"Satnam Dlay","orcid":null},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Satnam S. Dlay","raw_affiliation_strings":["Newcastle University, Newcastle upon Tyne, Tyne and Wear, GB"],"affiliations":[{"raw_affiliation_string":"Newcastle University, Newcastle upon Tyne, Tyne and Wear, GB","institution_ids":["https://openalex.org/I84884186"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083892296","display_name":"Jonathon A. Chambers","orcid":"https://orcid.org/0000-0002-5820-6509"},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jonathon A. Chambers","raw_affiliation_strings":["Newcastle University, Newcastle upon Tyne, Tyne and Wear, GB"],"affiliations":[{"raw_affiliation_string":"Newcastle University, Newcastle upon Tyne, Tyne and Wear, GB","institution_ids":["https://openalex.org/I84884186"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5053424993"],"corresponding_institution_ids":["https://openalex.org/I84884186"],"apc_list":null,"apc_paid":null,"fwci":1.0392,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.82788913,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9995999932289124,"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":0.9829000234603882,"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":0.7711070775985718},{"id":"https://openalex.org/keywords/timit","display_name":"TIMIT","score":0.7390641570091248},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.7304772734642029},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6349930167198181},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.63164222240448},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6156147122383118},{"id":"https://openalex.org/keywords/speaker-identification","display_name":"Speaker identification","score":0.5934286713600159},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5925287008285522},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5417453050613403},{"id":"https://openalex.org/keywords/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.48153620958328247},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4678391218185425},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46013444662094116},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.44492557644844055},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.41406679153442383},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.264447957277298},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.21568498015403748},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10732686519622803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7711070775985718},{"id":"https://openalex.org/C2778724510","wikidata":"https://www.wikidata.org/wiki/Q7670405","display_name":"TIMIT","level":3,"score":0.7390641570091248},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.7304772734642029},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6349930167198181},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.63164222240448},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6156147122383118},{"id":"https://openalex.org/C2986627078","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker identification","level":3,"score":0.5934286713600159},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5925287008285522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5417453050613403},{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.48153620958328247},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4678391218185425},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46013444662094116},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.44492557644844055},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.41406679153442383},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.264447957277298},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.21568498015403748},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10732686519622803},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iwbf.2017.7935102","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iwbf.2017.7935102","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 5th International Workshop on Biometrics and Forensics (IWBF)","raw_type":"proceedings-article"},{"id":"pmh:oai:nrl.northumbria.ac.uk:38619","is_oa":false,"landing_page_url":"http://nrl.northumbria.ac.uk/38619/","pdf_url":null,"source":{"id":"https://openalex.org/S4306401884","display_name":"Northumbria Research Link (Northumbria University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32394136","host_organization_name":"Northumbria University","host_organization_lineage":["https://openalex.org/I32394136"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Book Section"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.47999998927116394}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322727","display_name":"Minist\u00e8re de l'Education Nationale, de l'Enseignement Superieur et de la Recherche","ror":"https://ror.org/03sjk9a61"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W133071504","https://openalex.org/W1163572983","https://openalex.org/W1607650603","https://openalex.org/W2000447741","https://openalex.org/W2001954572","https://openalex.org/W2040202932","https://openalex.org/W2048014685","https://openalex.org/W2069883713","https://openalex.org/W2080794664","https://openalex.org/W2081620461","https://openalex.org/W2090160423","https://openalex.org/W2101412703","https://openalex.org/W2127066119","https://openalex.org/W2143944641","https://openalex.org/W2150769028","https://openalex.org/W2162416585","https://openalex.org/W2165880886","https://openalex.org/W2334935959","https://openalex.org/W2404874347","https://openalex.org/W2407857848","https://openalex.org/W2465929418","https://openalex.org/W2513087016","https://openalex.org/W2994602700","https://openalex.org/W4233464001","https://openalex.org/W6671024424","https://openalex.org/W6713414053"],"related_works":["https://openalex.org/W3119288895","https://openalex.org/W4234190324","https://openalex.org/W2185075503","https://openalex.org/W2092874659","https://openalex.org/W4396668120","https://openalex.org/W2101922478","https://openalex.org/W2186375278","https://openalex.org/W2749720872","https://openalex.org/W2126085626","https://openalex.org/W3204851989"],"abstract_inverted_index":{"Physiological":[0],"and":[1,9,35,51,77,100,106],"behavioural":[2],"human":[3],"characteristics":[4],"are":[5,12],"exploited":[6],"in":[7,109],"biometrics":[8],"performance":[10],"metrics":[11],"used":[13],"to":[14,25,56,81,111],"measure":[15,22],"some":[16],"characteristic":[17],"of":[18,54,62,66],"an":[19,67,83],"individual.":[20],"The":[21,59,89,137],"might":[23],"lead":[24],"a":[26,36,45,113,131],"one-to-one":[27],"match,":[28],"which":[29],"is":[30,78,91],"called":[31],"authentication":[32],"or":[33],"one-from-N,":[34],"match":[37],"represents":[38],"identification.":[39],"In":[40],"this":[41],"paper,":[42],"we":[43],"exploit":[44],"speech":[46],"biometric":[47],"I-vector":[48,68],"with":[49,69,93,116,130,144],"low":[50,75],"fixed":[52],"dimension":[53],"100":[55],"identify":[57],"speakers.":[58],"main":[60],"structure":[61],"the":[63,104,122,145],"system":[64,90,138],"consists":[65],"three":[70],"fusion":[71],"methods.":[72],"It":[73],"has":[74],"complexity":[76],"efficient":[79],"due":[80],"using":[82],"Extreme":[84],"Learning":[85],"Machine":[86],"(ELM)":[87],"classifier.":[88],"evaluated":[92],"120":[94],"speakers":[95],"from":[96,102],"dialect":[97],"regions":[98],"one":[99],"four":[101],"both":[103],"TIMIT":[105],"NTIMIT":[107],"databases":[108],"order":[110],"provide":[112],"fair":[114],"comparison":[115],"our":[117],"previous":[118],"study":[119],"based":[120],"on":[121],"traditional":[123],"Gaussian":[124],"Mixture":[125],"Model-Universal":[126],"Background":[127],"Model":[128],"(GMM-UBM)":[129],"Maximum":[132],"Likelihood":[133],"(ML)":[134],"classifier":[135],"system.":[136],"shows":[139],"identification":[140],"rate":[141],"improvement":[142],"compared":[143],"classical":[146],"GMM-UBM.":[147]},"counts_by_year":[{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
