{"id":"https://openalex.org/W2156142001","doi":"https://doi.org/10.1109/89.661472","title":"Continuous probabilistic transform for voice conversion","display_name":"Continuous probabilistic transform for voice conversion","publication_year":1998,"publication_date":"1998-03-01","ids":{"openalex":"https://openalex.org/W2156142001","doi":"https://doi.org/10.1109/89.661472","mag":"2156142001"},"language":"en","primary_location":{"id":"doi:10.1109/89.661472","doi":"https://doi.org/10.1109/89.661472","is_oa":false,"landing_page_url":"https://doi.org/10.1109/89.661472","pdf_url":null,"source":{"id":"https://openalex.org/S202446260","display_name":"IEEE Transactions on Speech and Audio Processing","issn_l":"1063-6676","issn":["1063-6676","1558-2353"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Speech and Audio Processing","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W2156142001"],"child_works_count":0,"type":"article","is_traditional":true,"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/A5035745788","display_name":"Yannis Stylianou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Y. Stylianou","raw_affiliation_strings":["AT and T Research Laboratories, Murray Hill, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AT and T Research Laboratories, Murray Hill, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105628617","display_name":"Olivier Capp\u00e9","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"O. Cappe","raw_affiliation_strings":["D\u00e9partement Signal/CNRS-URA 820, Ecole Nationale Sup\u00e9rieure des T\u00e9I\u00e9communications, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"D\u00e9partement Signal/CNRS-URA 820, Ecole Nationale Sup\u00e9rieure des T\u00e9I\u00e9communications, Paris, France","institution_ids":["https://openalex.org/I12356871","https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101398712","display_name":"\u00c9ric Moulines","orcid":"https://orcid.org/0000-0002-2058-0693","observed_orcids":["https://orcid.org/0000-0002-2058-0693"]},"institutions":[{"id":"https://openalex.org/I12356871","display_name":"T\u00e9l\u00e9com Paris","ror":"https://ror.org/01naq7912","country_code":"FR","type":"education","lineage":["https://openalex.org/I12356871","https://openalex.org/I205703379","https://openalex.org/I4210145102"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"E. Moulines","raw_affiliation_strings":["D\u00e9partement Signal/CNRS-URA 820, Ecole Nationale Sup\u00e9rieure des T\u00e9I\u00e9communications, Paris, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"D\u00e9partement Signal/CNRS-URA 820, Ecole Nationale Sup\u00e9rieure des T\u00e9I\u00e9communications, Paris, France","institution_ids":["https://openalex.org/I12356871","https://openalex.org/I1294671590"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3073,"has_fulltext":false,"cited_by_count":940,"citation_normalized_percentile":{"value":0.8776985,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"6","issue":"2","first_page":"131","last_page":"142"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9678000211715698,"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":0.9678000211715698,"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":0.031300000846385956,"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/T10863","display_name":"Voice and Speech Disorders","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/3616","display_name":"Speech and Hearing"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/voice-conversion","display_name":"voice conversion","score":0.9869999885559082},{"id":"https://openalex.org/keywords/gaussian-mixture-model","display_name":"Gaussian mixture model","score":0.9419999718666077},{"id":"https://openalex.org/keywords/parametric-speech-synthesis","display_name":"parametric speech synthesis","score":0.5759999752044678},{"id":"https://openalex.org/keywords/probabilistic-classification","display_name":"probabilistic classification","score":0.75},{"id":"https://openalex.org/keywords/least-squares-estimation","display_name":"least squares estimation","score":0.6539999842643738}],"concepts":[{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7102876901626587},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6968233585357666},{"id":"https://openalex.org/C134537474","wikidata":"https://www.wikidata.org/wiki/Q17144832","display_name":"Naturalness","level":2,"score":0.6073366403579712},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.521430492401123},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.515882134437561},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.5012896060943604},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4777195453643799},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.42966634035110474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2937074899673462},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2429857850074768},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08211013674736023},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/89.661472","doi":"https://doi.org/10.1109/89.661472","is_oa":false,"landing_page_url":"https://doi.org/10.1109/89.661472","pdf_url":null,"source":{"id":"https://openalex.org/S202446260","display_name":"IEEE Transactions on Speech and Audio Processing","issn_l":"1063-6676","issn":["1063-6676","1558-2353"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Speech and Audio Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322892","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W93048866","https://openalex.org/W95551363","https://openalex.org/W167578630","https://openalex.org/W174669002","https://openalex.org/W250076511","https://openalex.org/W334543337","https://openalex.org/W1560013842","https://openalex.org/W1925249181","https://openalex.org/W1963778986","https://openalex.org/W1965392255","https://openalex.org/W1970763740","https://openalex.org/W1981367467","https://openalex.org/W1992468098","https://openalex.org/W1999405202","https://openalex.org/W2008957275","https://openalex.org/W2011916518","https://openalex.org/W2013996527","https://openalex.org/W2016520419","https://openalex.org/W2033516035","https://openalex.org/W2040266692","https://openalex.org/W2041326643","https://openalex.org/W2049633694","https://openalex.org/W2053742104","https://openalex.org/W2064844706","https://openalex.org/W2070513494","https://openalex.org/W2071850795","https://openalex.org/W2075665712","https://openalex.org/W2084134149","https://openalex.org/W2088562567","https://openalex.org/W2088632526","https://openalex.org/W2109114466","https://openalex.org/W2110007337","https://openalex.org/W2110420312","https://openalex.org/W2111748458","https://openalex.org/W2114180153","https://openalex.org/W2118850452","https://openalex.org/W2121407732","https://openalex.org/W2122159244","https://openalex.org/W2129967803","https://openalex.org/W2130418280","https://openalex.org/W2134383396","https://openalex.org/W2136833314","https://openalex.org/W2155199877","https://openalex.org/W2165880886","https://openalex.org/W2169325501","https://openalex.org/W2170120409","https://openalex.org/W2518483182","https://openalex.org/W2989457786","https://openalex.org/W3017143921","https://openalex.org/W4300515658","https://openalex.org/W4300956553"],"related_works":["https://openalex.org/W2096564043","https://openalex.org/W2120605154","https://openalex.org/W190419602","https://openalex.org/W2041448063","https://openalex.org/W2032421775","https://openalex.org/W2120731853","https://openalex.org/W2138640170","https://openalex.org/W1542472901","https://openalex.org/W2031095515","https://openalex.org/W2165625885"],"abstract_inverted_index":{"Voice":[0],"conversion,":[1],"as":[2,9,23],"considered":[3],"in":[4,116,145],"this":[5],"paper,":[6],"is":[7,57,76,114],"defined":[8],"modifying":[10],"the":[11,38,46,60,68,87,92,98,108,117,120,140,151,155,168,173,178],"speech":[12,130,180],"signal":[13],"of":[14,40,51,62,67,97,119,129,177],"one":[15],"speaker":[16,32,70],"(source":[17],"speaker)":[18],"so":[19],"that":[20,167],"it":[21,25],"sounds":[22],"if":[24],"had":[26],"been":[27],"pronounced":[28],"by":[29,78,91,103,159],"a":[30,41,63,79,146],"different":[31],"(target":[33],"speaker).":[34],"Our":[35],"contribution":[36],"includes":[37],"design":[39],"new":[42],"methodology":[43],"for":[44],"representing":[45],"relationship":[47],"between":[48,150],"two":[49],"sets":[50],"spectral":[52,71],"envelopes.":[53,72,157],"The":[54,73,95],"proposed":[55,141,169,185],"method":[56,113],"based":[58,136],"on":[59,107,137],"use":[61],"Gaussian":[64],"mixture":[65,93],"model":[66],"source":[69],"conversion":[74,99,112,142,186],"itself":[75],"represented":[77],"continuous":[80],"parametric":[81],"function":[82,100],"which":[83,125],"takes":[84],"into":[85],"account":[86],"probabilistic":[88],"classification":[89],"provided":[90],"model.":[94],"parameters":[96],"are":[101],"estimated":[102],"least":[104],"squares":[105],"optimization":[106],"training":[109],"data.":[110],"This":[111],"implemented":[115],"context":[118],"HNM":[121],"(harmonic+noise":[122],"model)":[123],"system,":[124],"allows":[126],"high-quality":[127],"modifications":[128],"signals.":[131],"Compared":[132],"to":[133],"earlier":[134],"methods":[135],"vector":[138],"quantization,":[139],"scheme":[143],"results":[144],"much":[147],"better":[148],"match":[149],"converted":[152,179],"envelopes":[153],"and":[154,162,175],"target":[156],"Evaluation":[158],"objective":[160],"tests":[161,165],"formal":[163],"listening":[164],"shows":[166],"transform":[170],"greatly":[171],"improves":[172],"quality":[174],"naturalness":[176],"signals":[181],"compared":[182],"with":[183],"previous":[184],"methods.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":22},{"year":2021,"cited_by_count":42},{"year":2020,"cited_by_count":55},{"year":2019,"cited_by_count":61},{"year":2018,"cited_by_count":39},{"year":2017,"cited_by_count":54},{"year":2016,"cited_by_count":55},{"year":2015,"cited_by_count":58},{"year":2014,"cited_by_count":80},{"year":2013,"cited_by_count":62},{"year":2012,"cited_by_count":45}],"updated_date":"2026-11-13T13:42:25.865203","created_date":"2016-06-24T00:00:00"}
