{"id":"https://openalex.org/W1495955104","doi":"https://doi.org/10.21437/eurospeech.1997-346","title":"A lognormal tied mixture model of pitch for prosody based speaker recognition","display_name":"A lognormal tied mixture model of pitch for prosody based speaker recognition","publication_year":1997,"publication_date":"1997-09-22","ids":{"openalex":"https://openalex.org/W1495955104","doi":"https://doi.org/10.21437/eurospeech.1997-346","mag":"1495955104"},"language":"en","primary_location":{"id":"doi:10.21437/eurospeech.1997-346","is_oa":false,"landing_page_url":"https://doi.org/10.21437/eurospeech.1997-346","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"5th European Conference on Speech Communication and Technology (Eurospeech 1997)","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/A5023103090","display_name":"Kemal S\u00f6nmez","orcid":"https://orcid.org/0000-0002-2816-6438"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"M. Kemal S\u00f6nmez","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003679010","display_name":"Larry Heck","orcid":"https://orcid.org/0000-0003-3358-6362"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Larry Heck","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108513736","display_name":"M. Weintraub","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mitchel Weintraub","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5107174154","display_name":"Elizabeth Shriberg","orcid":"https://orcid.org/0009-0004-3779-4956"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elizabeth Shriberg","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023103090"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7551,"has_fulltext":false,"cited_by_count":85,"citation_normalized_percentile":{"value":0.85422133,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1391","last_page":"1394"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9986000061035156,"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":0.9760000109672546,"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/speech-recognition","display_name":"Speech recognition","score":0.6835479736328125},{"id":"https://openalex.org/keywords/cepstrum","display_name":"Cepstrum","score":0.6186490058898926},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5659499168395996},{"id":"https://openalex.org/keywords/log-normal-distribution","display_name":"Log-normal distribution","score":0.5653319954872131},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.47249189019203186},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4503468871116638},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.43803077936172485},{"id":"https://openalex.org/keywords/constant-false-alarm-rate","display_name":"Constant false alarm rate","score":0.4176537096500397},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4092055857181549},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.40022021532058716},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32272565364837646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.301969975233078}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6835479736328125},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.6186490058898926},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5659499168395996},{"id":"https://openalex.org/C151620405","wikidata":"https://www.wikidata.org/wiki/Q826116","display_name":"Log-normal distribution","level":2,"score":0.5653319954872131},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.47249189019203186},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4503468871116638},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.43803077936172485},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.4176537096500397},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4092055857181549},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.40022021532058716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32272565364837646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.301969975233078}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/eurospeech.1997-346","is_oa":false,"landing_page_url":"https://doi.org/10.21437/eurospeech.1997-346","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"5th European Conference on Speech Communication and Technology (Eurospeech 1997)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W1751091532","https://openalex.org/W1991567646","https://openalex.org/W2001697496","https://openalex.org/W2147592170"],"related_works":["https://openalex.org/W2100203012","https://openalex.org/W2353790262","https://openalex.org/W2368338897","https://openalex.org/W2893674991","https://openalex.org/W1983393909","https://openalex.org/W2040150569","https://openalex.org/W2468095590","https://openalex.org/W2132174924","https://openalex.org/W1911540634","https://openalex.org/W2013909972"],"abstract_inverted_index":{"Statistics":[0],"of":[1,16,25,31,43,49,108,115,127,152,162],"pitch":[2,26,32,44,50,53,78,100,103,135],"have":[3],"recently":[4],"been":[5],"used":[6],"in":[7,28,105,139,183,194],"speaker":[8,140],"recognition":[9],"systems":[10,18],"with":[11,81,119,168],"good":[12],"results.":[13],"The":[14],"success":[15],"such":[17],"depends":[19],"on":[20,142,157],"robust":[21],"and":[22,70,122,154,175,191],"accurate":[23],"computation":[24],"statistics":[27,51,136,179],"the":[29,87,106,133,143,158,163,165,173,203],"presence":[30,107],"tracking":[33],"errors.":[34],"In":[35],"this":[36],"work,":[37],"we":[38,93],"develop":[39],"a":[40,66,82,95,102,113,125],"statistical":[41],"model":[42,69,97],"that":[45,76],"allows":[46],"unbiased":[47],"estimation":[48],"from":[52],"tracks":[54],"which":[55,110],"are":[56],"subject":[57],"to":[58,112],"doubling":[59],"and/or":[60],"halving.":[61],"We":[62,131],"first":[63],"argue":[64],"by":[65,73],"simple":[67],"correlation":[68],"empirically":[71],"demonstrate":[72],"QQ":[74],"plots":[75],"\u201cclean\u201d":[77],"is":[79],"distributed":[80],"lognormal":[83,117],"distribution":[84],"rather":[85],"than":[86],"often":[88],"assumed":[89],"normal":[90],"distribution.":[91],"Second,":[92],"present":[94],"probabilistic":[96],"for":[98,124,171],"estimated":[99],"via":[101],"tracker":[104],"doubling/halving,":[109],"leads":[111],"mixture":[114],"three":[116],"distributions":[118],"tied":[120],"means":[121],"variances":[123],"total":[126],"four":[128],"free":[129],"parameters.":[130],"use":[132],"obtained":[134],"as":[137],"features":[138],"verification":[141],"March":[144],"1996":[145],"NIST":[146],"Speaker":[147],"Recognition":[148],"Evaluation":[149],"data":[150],"(subset":[151],"Switchboard)":[153],"report":[155],"results":[156],"most":[159],"difficult":[160],"portion":[161],"database:":[164],"\u201cone-session\u201d":[166],"condition":[167],"males":[169],"only":[170],"both":[172],"claimant":[174],"imposter":[176],"speakers.":[177],"Pitch":[178],"provide":[180],"22%":[181],"reduction":[182,193],"false":[184,195],"alarm":[185,196],"rate":[186,190,197,201],"at":[187,198],"1%":[188],"miss":[189,200],"11%":[192],"10%":[199],"over":[202],"cepstrum-only":[204],"system.":[205]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
