{"id":"https://openalex.org/W2162471146","doi":"https://doi.org/10.1109/icassp.2008.4518560","title":"A multi-class MLLR kernel for SVM speaker recognition","display_name":"A multi-class MLLR kernel for SVM speaker recognition","publication_year":2008,"publication_date":"2008-03-01","ids":{"openalex":"https://openalex.org/W2162471146","doi":"https://doi.org/10.1109/icassp.2008.4518560","mag":"2162471146"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2008.4518560","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2008.4518560","pdf_url":null,"source":{"id":"https://openalex.org/S4210167542","display_name":"Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing","issn_l":"1520-6149","issn":["1520-6149","2379-190X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","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/A5024845779","display_name":"Zahi N. Karam","orcid":"https://orcid.org/0000-0003-1409-5488"},"institutions":[{"id":"https://openalex.org/I4210122954","display_name":"MIT Lincoln Laboratory","ror":"https://ror.org/022z6jk58","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210122954","https://openalex.org/I63966007"]},{"id":"https://openalex.org/I4210121626","display_name":"Signal Processing (United States)","ror":"https://ror.org/021gzyw51","country_code":"US","type":"company","lineage":["https://openalex.org/I4210121626"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zahi N. Karam","raw_affiliation_strings":["MIT Digital Signal Processing Group, Cambridge, MA, USA","MIT Lincoln Laboratories, Lexington, MA, USA"],"affiliations":[{"raw_affiliation_string":"MIT Digital Signal Processing Group, Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210121626"]},{"raw_affiliation_string":"MIT Lincoln Laboratories, Lexington, MA, USA","institution_ids":["https://openalex.org/I4210122954"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061064027","display_name":"William M. Campbell","orcid":"https://orcid.org/0000-0003-1657-5872"},"institutions":[{"id":"https://openalex.org/I4210122954","display_name":"MIT Lincoln Laboratory","ror":"https://ror.org/022z6jk58","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210122954","https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William M. Campbell","raw_affiliation_strings":["MIT Lincoln Laboratories, Lexington, MA, USA"],"affiliations":[{"raw_affiliation_string":"MIT Lincoln Laboratories, Lexington, MA, USA","institution_ids":["https://openalex.org/I4210122954"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5024845779"],"corresponding_institution_ids":["https://openalex.org/I4210121626","https://openalex.org/I4210122954"],"apc_list":null,"apc_paid":null,"fwci":5.809,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.97266314,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4117","last_page":"4120"},"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":0.9991000294685364,"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":0.9975000023841858,"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/nist","display_name":"NIST","score":0.695042610168457},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6918792724609375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6819003224372864},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6690251231193542},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6552638411521912},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6208391785621643},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6155576109886169},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5552416443824768},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4888448119163513},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.4751853048801422},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.468680202960968},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43434858322143555},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.420421838760376},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16513821482658386}],"concepts":[{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.695042610168457},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6918792724609375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6819003224372864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6690251231193542},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6552638411521912},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6208391785621643},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6155576109886169},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5552416443824768},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4888448119163513},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.4751853048801422},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.468680202960968},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43434858322143555},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.420421838760376},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16513821482658386},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icassp.2008.4518560","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2008.4518560","pdf_url":null,"source":{"id":"https://openalex.org/S4210167542","display_name":"Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing","issn_l":"1520-6149","issn":["1520-6149","2379-190X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.295.1528","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.295.1528","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.ll.mit.edu/mission/communications/ist/publications/080330_CampbellW_ICASSP_MLLR.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.527.6071","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.527.6071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.rle.mit.edu/dspg/documents/ICASSP_2008.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W88081813","https://openalex.org/W1245633889","https://openalex.org/W1486089539","https://openalex.org/W2012908927","https://openalex.org/W2037740282","https://openalex.org/W2141279928","https://openalex.org/W2147147599","https://openalex.org/W2187693774","https://openalex.org/W2400705412","https://openalex.org/W3168666720","https://openalex.org/W4285719527","https://openalex.org/W6628066830","https://openalex.org/W6681823618"],"related_works":["https://openalex.org/W2158491338","https://openalex.org/W2807901368","https://openalex.org/W2133733652","https://openalex.org/W2072658171","https://openalex.org/W2606392311","https://openalex.org/W2320042380","https://openalex.org/W4385956668","https://openalex.org/W4324119469","https://openalex.org/W2164868312","https://openalex.org/W2160650576"],"abstract_inverted_index":{"Speaker":[0],"recognition":[1],"using":[2],"support":[3],"vector":[4],"machines":[5],"(SVMs)":[6],"with":[7,105,159],"features":[8,34],"derived":[9],"from":[10],"generative":[11],"models":[12],"has":[13,72],"been":[14],"shown":[15],"to":[16,27,63,86,122,131],"perform":[17],"well.":[18],"Typically,":[19],"a":[20,31,49,80,119],"universal":[21],"background":[22],"model":[23,52],"(UBM)":[24],"is":[25,48,61,84,157],"adapted":[26],"each":[28,123],"utterance":[29],"yielding":[30],"set":[32],"of":[33,67,91,161],"that":[35,100,144,152],"are":[36],"used":[37,62],"in":[38],"an":[39],"SVM.":[40],"We":[41],"consider":[42],"the":[43,46,65,68,77,88,92,111,128,132,138,153,162],"case":[44,78],"where":[45,79],"UBM":[47,112],"Gaussian":[50],"mixture":[51,89,113],"(GMM),":[53],"and":[54,117,151],"maximum":[55],"likelihood":[56],"linear":[57],"regression":[58],"(MLLR)":[59],"adaptation":[60],"adapt":[64],"means":[66],"UBM.":[69,94],"Recent":[70],"work":[71,96],"examined":[73],"this":[74,103],"setup":[75,104],"for":[76],"global":[81,149],"MLLR":[82,107,146,150],"transform":[83,121],"applied":[85],"all":[87],"components":[90,114],"QMM":[93],"This":[95,125],"produced":[97],"positive":[98],"results":[99],"warrant":[101],"examining":[102],"multi-class":[106,145],"adaptation,":[108],"which":[109],"groups":[110],"into":[115],"classes":[116],"applies":[118],"different":[120],"class.":[124],"paper":[126],"extends":[127],"MLLR/GMM":[129],"framework":[130],"multi-":[133],"class":[134],"case.":[135],"Experiments":[136],"on":[137,148],"NIST":[139],"SRE":[140],"2006":[141],"corpus":[142],"show":[143],"improves":[147],"proposed":[154],"system's":[155],"performance":[156],"comparable":[158],"state":[160],"art":[163],"systems.":[164]},"counts_by_year":[{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":8},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
