{"id":"https://openalex.org/W205715793","doi":"https://doi.org/10.21437/interspeech.2008-399","title":"Analysis of subspace within-class covariance normalization for SVM-based speaker verification","display_name":"Analysis of subspace within-class covariance normalization for SVM-based speaker verification","publication_year":2008,"publication_date":"2008-09-22","ids":{"openalex":"https://openalex.org/W205715793","doi":"https://doi.org/10.21437/interspeech.2008-399","mag":"205715793"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2008-399","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2008-399","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2008","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.pure.ed.ac.uk/ws/files/25681964/i08_1373.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101607148","display_name":"Liang Lu","orcid":"https://orcid.org/0000-0003-4005-679X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liang Lu","raw_affiliation_strings":["School of Informatics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Informatics","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056136429","display_name":"Yuan Dong","orcid":"https://orcid.org/0009-0004-8650-1603"},"institutions":[{"id":"https://openalex.org/I19370010","display_name":"Orange (France)","ror":"https://ror.org/035j0tq82","country_code":"FR","type":"company","lineage":["https://openalex.org/I19370010"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Yuan Dong","raw_affiliation_strings":["Orange (France), Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Orange (France), Paris, France","institution_ids":["https://openalex.org/I19370010"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100518039","display_name":"Xianyu Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I19370010","display_name":"Orange (France)","ror":"https://ror.org/035j0tq82","country_code":"FR","type":"company","lineage":["https://openalex.org/I19370010"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Xianyu Zhao","raw_affiliation_strings":["Orange (France), Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Orange (France), Paris, France","institution_ids":["https://openalex.org/I19370010"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078587654","display_name":"Jian Zhao","orcid":"https://orcid.org/0000-0002-3508-756X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Zhao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040729818","display_name":"Chengyu Dong","orcid":"https://orcid.org/0000-0001-9698-5884"},"institutions":[{"id":"https://openalex.org/I19370010","display_name":"Orange (France)","ror":"https://ror.org/035j0tq82","country_code":"FR","type":"company","lineage":["https://openalex.org/I19370010"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Chengyu Dong","raw_affiliation_strings":["France Telecom Research & Development Center, Beijing, 100083, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"France Telecom Research & Development Center, Beijing, 100083, China","institution_ids":["https://openalex.org/I19370010"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078897088","display_name":"Haila Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I19370010","display_name":"Orange (France)","ror":"https://ror.org/035j0tq82","country_code":"FR","type":"company","lineage":["https://openalex.org/I19370010"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Haila Wang","raw_affiliation_strings":["Orange (France), Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Orange (France), Paris, France","institution_ids":["https://openalex.org/I19370010"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5878,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.76616648,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1373","last_page":"1376"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9901999831199646,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9473999738693237,"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/normalization","display_name":"Normalization (sociology)","score":0.8216937780380249},{"id":"https://openalex.org/keywords/speaker-verification","display_name":"Speaker verification","score":0.7272502183914185},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6613324880599976},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6602618098258972},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6122700572013855},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5975356101989746},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.5857589244842529},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5538017749786377},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.47695744037628174},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4218841791152954},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.39746326208114624},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2286960780620575},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10995852947235107}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.8216937780380249},{"id":"https://openalex.org/C2982762665","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker verification","level":3,"score":0.7272502183914185},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6613324880599976},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6602618098258972},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6122700572013855},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5975356101989746},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.5857589244842529},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5538017749786377},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.47695744037628174},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4218841791152954},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.39746326208114624},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2286960780620575},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10995852947235107},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.21437/interspeech.2008-399","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2008-399","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2008","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.ed.ac.uk:publications/4f4c8639-3972-468b-a35b-ede2a7c647ce","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/portal/en/publications/analysis-of-subspace-withinclass-covariance-normalization-for-svmbased-speaker-verification(4f4c8639-3972-468b-a35b-ede2a7c647ce).html","pdf_url":"https://www.pure.ed.ac.uk/ws/files/25681964/i08_1373.pdf","source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","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":""},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.413.9895","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.413.9895","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://homepages.inf.ed.ac.uk/llu/pdf/analysis.pdf","raw_type":"text"},{"id":"pmh:oai:pure.ed.ac.uk:openaire/4f4c8639-3972-468b-a35b-ede2a7c647ce","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/4f4c8639-3972-468b-a35b-ede2a7c647ce","pdf_url":null,"source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Lu, L, Dong, Y, Zhao, X, Zhao, J, Dong, C & Wang, H 2008, Analysis of subspace within-class covariance normalization for SVM-based speaker verification. in INTERSPEECH 2008, 9th Annual Conference of the International Speech Communication Association, Brisbane, Australia, September 22-26, 2008. pp. 1373-1376, INTERSPEECH 2008 - 9th Annual Conference of the International Speech Communication Association, Brisbane, Australia, 22/09/08. < http://www.isca-speech.org/archive/interspeech_2008/i08_1373.html >","raw_type":"contributionToPeriodical"}],"best_oa_location":{"id":"pmh:oai:pure.ed.ac.uk:publications/4f4c8639-3972-468b-a35b-ede2a7c647ce","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/portal/en/publications/analysis-of-subspace-withinclass-covariance-normalization-for-svmbased-speaker-verification(4f4c8639-3972-468b-a35b-ede2a7c647ce).html","pdf_url":"https://www.pure.ed.ac.uk/ws/files/25681964/i08_1373.pdf","source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","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":""},"sustainable_development_goals":[{"score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W205715793.pdf","grobid_xml":"https://content.openalex.org/works/W205715793.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W32477078","https://openalex.org/W90661335","https://openalex.org/W1553271421","https://openalex.org/W1916834241","https://openalex.org/W2002123483","https://openalex.org/W2108948497","https://openalex.org/W2115005074","https://openalex.org/W2121647436","https://openalex.org/W2134354815","https://openalex.org/W2144760012","https://openalex.org/W2146871184","https://openalex.org/W2148554390","https://openalex.org/W2177287823"],"related_works":["https://openalex.org/W1968216131","https://openalex.org/W2355011896","https://openalex.org/W3089964815","https://openalex.org/W1581134722","https://openalex.org/W66821593","https://openalex.org/W1521299571","https://openalex.org/W2169890399","https://openalex.org/W2170952763","https://openalex.org/W2359348847","https://openalex.org/W4235705411"],"abstract_inverted_index":{"Nuisance":[0],"attribute":[1],"projection":[2],"(NAP)":[3],"and":[4,96],"within-class":[5],"covariance":[6],"normalization":[7],"(WCCN)":[8],"are":[9],"two":[10],"effective":[11],"techniques":[12],"for":[13,57],"intersession":[14],"variability":[15,34],"compensation":[16],"in":[17,100,139],"SVM":[18],"based":[19],"speaker":[20],"verification":[21],"systems.":[22],"However,":[23],"by":[24,94],"normalizing":[25],"or":[26],"removing":[27],"the":[28,32,40,49,63,77,84,101,106,130,134],"nuisance":[29],"subspace":[30,78,93,107,121,131],"containing":[31],"session":[33],"can":[35,109],"not":[36],"guarantee":[37],"to":[38],"enlarge":[39],"distance":[41],"between":[42],"speakers.":[43],"In":[44],"this":[45],"paper,":[46],"we":[47,75,119],"investigated":[48],"probability":[50],"of":[51,115],"using":[52,72],"linear":[53],"discriminant":[54],"analysis":[55],"(LDA)":[56],"discriminative":[58],"training.":[59],"To":[60],"cope":[61],"with":[62],"small":[64],"sample":[65],"size":[66],"problem":[67],"which":[68,81,118],"prevents":[69],"us":[70],"from":[71],"LDA":[73,79,99,108],"directly,":[74],"adapted":[76],"approach,":[80,117],"first":[82],"projects":[83],"whole":[85],"feature":[86,142],"space":[87],"into":[88,112],"a":[89,113],"relatively":[90],"low":[91,140],"dimensional":[92,141],"PCA,":[95],"then":[97],"performs":[98],"subspace.":[102],"By":[103],"some":[104],"modification,":[105],"be":[110],"degenerated":[111],"kind":[114],"WCCN":[116,132],"called":[120],"WCCN.":[122],"Experiments":[123],"on":[124],"NIST":[125],"SRE":[126],"tasks":[127],"showed":[128],"that,":[129],"outperformed":[133],"conventional":[135],"direct":[136],"WCCN,":[137],"especially":[138],"space.":[143]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}