{"id":"https://openalex.org/W2241475445","doi":"https://doi.org/10.1109/fskd.2015.7382177","title":"Hierarchical speaker verification: Kernel fisher discriminant plus Mixed-PCA classifier and FCM clustering","display_name":"Hierarchical speaker verification: Kernel fisher discriminant plus Mixed-PCA classifier and FCM clustering","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W2241475445","doi":"https://doi.org/10.1109/fskd.2015.7382177","mag":"2241475445"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2015.7382177","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2015.7382177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","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/A5113916952","display_name":"Ping Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tan Ping","raw_affiliation_strings":["School of Digital Media, Lanzhou University of Arts and Science, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Digital Media, Lanzhou University of Arts and Science, Lanzhou, China","institution_ids":["https://openalex.org/I76214153"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xing Yujuan","orcid":null},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Yujuan","raw_affiliation_strings":["School of Digital Media, Lanzhou University of Arts and Science, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Digital Media, Lanzhou University of Arts and Science, Lanzhou, China","institution_ids":["https://openalex.org/I76214153"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76214153"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.08199893,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"5","issue":null,"first_page":"1561","last_page":"1565"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9904999732971191,"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":0.9904999732971191,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.9758999943733215,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.965399980545044,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.8123534917831421},{"id":"https://openalex.org/keywords/kernel-fisher-discriminant-analysis","display_name":"Kernel Fisher discriminant analysis","score":0.7687745094299316},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7092366814613342},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6929084658622742},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6183974742889404},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5978188514709473},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5903472900390625},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5851365327835083},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.49327319860458374},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.49188852310180664},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45144906640052795},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4410795271396637},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.43942010402679443},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.4187391698360443},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33788466453552246},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22584253549575806},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.0719180703163147}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.8123534917831421},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.7687745094299316},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7092366814613342},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6929084658622742},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6183974742889404},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5978188514709473},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5903472900390625},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5851365327835083},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.49327319860458374},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.49188852310180664},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45144906640052795},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4410795271396637},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.43942010402679443},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.4187391698360443},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33788466453552246},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22584253549575806},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.0719180703163147},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/fskd.2015.7382177","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2015.7382177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","raw_type":"proceedings-article"},{"id":"pmh:oai:ir.lzu.edu.cn/:262010/352733","is_oa":false,"landing_page_url":"http://ir.lzu.edu.cn/handle/262010/352733","pdf_url":null,"source":{"id":"https://openalex.org/S4406923049","display_name":"Lanzhou University Institutional Repository","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"\u4f1a\u8bae\u8bba\u6587"},{"id":"pmh:oai:ir.lzu.edu.cn/:262010/303648","is_oa":false,"landing_page_url":"http://ir.lzu.edu.cn/handle/262010/303648","pdf_url":null,"source":{"id":"https://openalex.org/S4406923049","display_name":"Lanzhou University Institutional Repository","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"\u4f1a\u8bae\u8bba\u6587"},{"id":"pmh:oai:ir.lzu.edu.cn/:262010/308394","is_oa":false,"landing_page_url":"http://ir.lzu.edu.cn/handle/262010/308394","pdf_url":null,"source":{"id":"https://openalex.org/S4406923049","display_name":"Lanzhou University Institutional Repository","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"\u4f1a\u8bae\u8bba\u6587"},{"id":"pmh:oai:ir.lzu.edu.cn/:262010/422731","is_oa":false,"landing_page_url":"https://ieeexplore.ieee.org/document/7382177/","pdf_url":null,"source":{"id":"https://openalex.org/S4406923049","display_name":"Lanzhou University Institutional Repository","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"\u4f1a\u8bae\u8bba\u6587"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1587559447","https://openalex.org/W1924165705","https://openalex.org/W1966223876","https://openalex.org/W1979357005","https://openalex.org/W1980987999","https://openalex.org/W1991519797","https://openalex.org/W1995450389","https://openalex.org/W1999785771","https://openalex.org/W2001003881","https://openalex.org/W2045956438","https://openalex.org/W2078953162","https://openalex.org/W2107284348","https://openalex.org/W2108948497","https://openalex.org/W2109531142","https://openalex.org/W2113908141","https://openalex.org/W2114644511","https://openalex.org/W2117864503","https://openalex.org/W2121750345","https://openalex.org/W2133324003","https://openalex.org/W2150769028","https://openalex.org/W2163771264","https://openalex.org/W2165918462","https://openalex.org/W2171428093","https://openalex.org/W2187416653","https://openalex.org/W4313169793","https://openalex.org/W6640228627","https://openalex.org/W6677071300","https://openalex.org/W6684810244"],"related_works":["https://openalex.org/W1963649114","https://openalex.org/W2538559652","https://openalex.org/W1978302214","https://openalex.org/W2162393942","https://openalex.org/W2068218029","https://openalex.org/W3147024994","https://openalex.org/W1741177776","https://openalex.org/W2025089370","https://openalex.org/W1984472287","https://openalex.org/W2022977822"],"abstract_inverted_index":{"In":[0,18,34,66],"order":[1],"to":[2,42,53,87,103],"improve":[3],"speaker":[4,12],"verification":[5,13],"accuracy,":[6],"we":[7,39],"proposed":[8,75,116],"a":[9,70],"new":[10],"hierarchical":[11,127],"algorithm":[14],"in":[15],"this":[16],"paper.":[17],"our":[19,115,126],"algorithm,":[20],"Mixed-PCA":[21],"plus":[22],"fuzzy":[23],"c-means":[24],"(FCM)":[25],"clustering":[26],"was":[27,51,74,98],"combined":[28],"with":[29],"kernel":[30],"fisher":[31],"discriminant":[32,56],"(KFD).":[33],"stage":[35,67],"of":[36,68,114],"feature":[37,45],"extraction,":[38],"exploited":[40],"PCA":[41],"reduce":[43],"the":[44,89,112,121],"vector":[46],"dimensions,":[47],"and":[48,58,82],"then":[49],"FCM":[50],"used":[52],"select":[54,88],"more":[55],"data":[57,61],"cluster":[59],"training":[60],"set":[62],"into":[63],"some":[64],"clusters.":[65],"recognition,":[69],"novel":[71],"MPCA":[72],"classifier":[73,102,128],"based":[76],"on":[77],"principal":[78],"component":[79],"space":[80,85],"(PCS)":[81],"truncation":[83],"error":[84],"(TES)":[86],"possible":[90],"R":[91],"target":[92,105],"speakers":[93],"fleetly.":[94],"And":[95,125],"then,":[96],"KFD":[97],"adopted":[99],"as":[100],"final":[101],"verify":[104],"speaker.":[106],"The":[107],"experimental":[108],"results":[109],"showed":[110],"that":[111],"EER":[113],"method":[117],"is":[118,123],"4.83%,":[119],"meanwhile":[120],"minDCF":[122],"0.0504.":[124],"has":[129],"shorter":[130],"recognition":[131],"time.":[132]},"counts_by_year":[{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
