{"id":"https://openalex.org/W2408608560","doi":"https://doi.org/10.21437/interspeech.2015-280","title":"Modified-prior PLDA and score calibration for duration mismatch compensation in speaker recognition system","display_name":"Modified-prior PLDA and score calibration for duration mismatch compensation in speaker recognition system","publication_year":2015,"publication_date":"2015-09-06","ids":{"openalex":"https://openalex.org/W2408608560","doi":"https://doi.org/10.21437/interspeech.2015-280","mag":"2408608560"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2015-280","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2015-280","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2015","raw_type":"proceedings-article"},"type":"conference-paper","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/A5011997254","display_name":"Qingyang Hong","orcid":"https://orcid.org/0000-0001-7380-8690"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"QingYang Hong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412926","display_name":"Lin Li","orcid":"https://orcid.org/0000-0003-0426-6546"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Li","raw_affiliation_strings":["[Xiamen University]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"[Xiamen University]","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351449","display_name":"Ming Li","orcid":"https://orcid.org/0000-0002-6406-1983"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ming Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082878554","display_name":"Ling Huang","orcid":"https://orcid.org/0000-0001-5089-4637"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ling Huang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101766015","display_name":"Lihong Wan","orcid":"https://orcid.org/0000-0003-2741-6615"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lihong Wan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100433188","display_name":"Jun Zhang","orcid":"https://orcid.org/0000-0002-6601-9180"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1037","last_page":"1041"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9912999868392944,"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":0.9553999900817871,"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":0.7542113661766052},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7111880779266357},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6744840145111084},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6642372608184814},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5980501770973206},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47568047046661377},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.4756205379962921},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4586082100868225},{"id":"https://openalex.org/keywords/duration","display_name":"Duration (music)","score":0.44958803057670593},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.41580018401145935}],"concepts":[{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.7542113661766052},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7111880779266357},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6744840145111084},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6642372608184814},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5980501770973206},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47568047046661377},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.4756205379962921},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4586082100868225},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.44958803057670593},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.41580018401145935},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2015-280","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2015-280","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2015","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7300000190734863,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1990942610","https://openalex.org/W2026358225","https://openalex.org/W2041823554","https://openalex.org/W2057888214","https://openalex.org/W2064364374","https://openalex.org/W2121812409","https://openalex.org/W2137286467","https://openalex.org/W2143694533","https://openalex.org/W2144411866","https://openalex.org/W2150769028","https://openalex.org/W2395750323","https://openalex.org/W2401095040","https://openalex.org/W2402704384"],"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/W2900895161","https://openalex.org/W4380838366","https://openalex.org/W3148366653"],"abstract_inverted_index":{"To":[0,104],"deal":[1],"with":[2,50,123],"the":[3,23,29,46,65,74,97,101,106,109,116,130,152,162,168],"performance":[4,169],"degradation":[5],"of":[6,28,52,108,132,144,154,170],"speaker":[7,171],"recognition":[8],"due":[9],"to":[10,21,95],"duration":[11,51,66,87,145,159],"mismatch":[12],"between":[13],"enrollment":[14],"and":[15,140,147,161],"test":[16,125,133],"utterances,":[17],"a":[18,90],"novel":[19],"strategy":[20],"modify":[22],"standard":[24],"normal":[25],"prior":[26],"distribution":[27],"i-vector":[30,75],"during":[31],"probabilistic":[32],"linear":[33,98],"discriminant":[34],"analysis":[35],"(PLDA)":[36],"modeling":[37],"is":[38,93],"employed.":[39],"This":[40],"new":[41],"modified-prior":[42,155],"PLDA":[43,156],"model":[44],"incorporates":[45],"covariance":[47],"matrix":[48],"scaled":[49],"each":[53,56],"utterance":[54,126],"for":[55],"speaker,":[57],"which":[58,85,129],"achieves":[59],"more":[60],"discriminative":[61],"characteristics":[62],"by":[63],"learning":[64],"variability":[67],"as":[68,70,89],"well":[69],"session":[71],"variation":[72,88],"in":[73,100,121,128,157],"space.":[76],"Furthermore,":[77],"an":[78],"efficient":[79],"Quality":[80],"Measure":[81],"Function":[82],"(QMF)":[83],"method":[84],"adopts":[86],"compensation":[91],"technique":[92],"employed":[94],"eliminate":[96],"shift":[99],"score":[102,164],"domain.":[103],"evaluate":[105],"robustness":[107],"proposed":[110],"approach,":[111],"experiments":[112],"were":[113,135],"conducted":[114],"on":[115],"NIST":[117],"SRE10":[118],"core-core":[119],"task":[120],"condition-5":[122],"varying":[124],"duration,":[127],"i-vectors":[131],"utterances":[134],"extracted":[136],"from":[137],"full":[138],"segment":[139],"randomly":[141],"truncated":[142],"segments":[143],"10s":[146],"20s.":[148],"The":[149],"results":[150],"demonstrated":[151],"efficiency":[153],"different":[158],"conditions,":[160],"combined":[163],"calibration":[165],"further":[166],"improved":[167],"recognition.":[172]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":12},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}