{"id":"https://openalex.org/W2608377413","doi":"https://doi.org/10.1109/icpr.2016.7900072","title":"Text-independent voice conversion using deep neural network based phonetic level features","display_name":"Text-independent voice conversion using deep neural network based phonetic level features","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2608377413","doi":"https://doi.org/10.1109/icpr.2016.7900072","mag":"2608377413"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7900072","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900072","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","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/A5007825677","display_name":"Huadi Zheng","orcid":"https://orcid.org/0000-0003-1224-9885"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Huadi Zheng","raw_affiliation_strings":["Dept. of EIE, Hong Kong Polytechnic University"],"affiliations":[{"raw_affiliation_string":"Dept. of EIE, Hong Kong Polytechnic University","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103888187","display_name":"Weicheng Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210129003","display_name":"SYSU-CMU International Joint Research Institute","ror":"https://ror.org/02w30ae27","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210129003"]},{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weicheng Cai","raw_affiliation_strings":["SYSU-CMU Joint Institute of Eng., Sun Yat-sen University"],"affiliations":[{"raw_affiliation_string":"SYSU-CMU Joint Institute of Eng., Sun Yat-sen University","institution_ids":["https://openalex.org/I4210129003","https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103218426","display_name":"Tianyan Zhou","orcid":"https://orcid.org/0000-0003-3238-2982"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210129003","display_name":"SYSU-CMU International Joint Research Institute","ror":"https://ror.org/02w30ae27","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210129003"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyan Zhou","raw_affiliation_strings":["SYSU-CMU Joint Institute of Eng., Sun Yat-sen University"],"affiliations":[{"raw_affiliation_string":"SYSU-CMU Joint Institute of Eng., Sun Yat-sen University","institution_ids":["https://openalex.org/I4210129003","https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023863527","display_name":"Shilei Zhang","orcid":"https://orcid.org/0009-0008-6755-7926"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shilei Zhang","raw_affiliation_strings":["Speech technology and Solution Group, IBM China Research"],"affiliations":[{"raw_affiliation_string":"Speech technology and Solution Group, IBM China Research","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100351449","display_name":"Ming Li","orcid":"https://orcid.org/0000-0002-6406-1983"},"institutions":[{"id":"https://openalex.org/I4210129003","display_name":"SYSU-CMU International Joint Research Institute","ror":"https://ror.org/02w30ae27","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210129003"]},{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Li","raw_affiliation_strings":["SYSU-CMU Joint Institute of Eng., Sun Yat-sen University","SYSU-CMU Shunde International Joint Research Institute"],"affiliations":[{"raw_affiliation_string":"SYSU-CMU Joint Institute of Eng., Sun Yat-sen University","institution_ids":["https://openalex.org/I4210129003","https://openalex.org/I157773358"]},{"raw_affiliation_string":"SYSU-CMU Shunde International Joint Research Institute","institution_ids":["https://openalex.org/I4210129003","https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5007825677"],"corresponding_institution_ids":["https://openalex.org/I14243506"],"apc_list":null,"apc_paid":null,"fwci":0.4434,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.81821399,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"22","issue":null,"first_page":"2872","last_page":"2877"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9948999881744385,"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":0.9933000206947327,"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/computer-science","display_name":"Computer science","score":0.8082481622695923},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7274059057235718},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6967141032218933},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5762856006622314},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5684630870819092},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5514125823974609},{"id":"https://openalex.org/keywords/speaker-recognition","display_name":"Speaker recognition","score":0.5448482036590576},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47776949405670166},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.45775899291038513},{"id":"https://openalex.org/keywords/speech-processing","display_name":"Speech processing","score":0.42468786239624023},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.42442643642425537},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4146724343299866}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8082481622695923},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7274059057235718},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6967141032218933},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5762856006622314},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5684630870819092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5514125823974609},{"id":"https://openalex.org/C133892786","wikidata":"https://www.wikidata.org/wiki/Q1145189","display_name":"Speaker recognition","level":2,"score":0.5448482036590576},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47776949405670166},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.45775899291038513},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.42468786239624023},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.42442643642425537},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4146724343299866},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2016.7900072","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900072","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:ira.lib.polyu.edu.hk:10397/75546","is_oa":false,"landing_page_url":"http://hdl.handle.net/10397/75546","pdf_url":null,"source":{"id":"https://openalex.org/S4306400205","display_name":"PolyU Institutional Research Archive (Hong Kong Polytechnic University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I14243506","host_organization_name":"Hong Kong Polytechnic University","host_organization_lineage":["https://openalex.org/I14243506"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6700000166893005,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W330298975","https://openalex.org/W996208672","https://openalex.org/W1519698338","https://openalex.org/W1977362459","https://openalex.org/W2009674825","https://openalex.org/W2022125261","https://openalex.org/W2026704977","https://openalex.org/W2039057510","https://openalex.org/W2049686551","https://openalex.org/W2105160541","https://openalex.org/W2111550316","https://openalex.org/W2114543868","https://openalex.org/W2114659828","https://openalex.org/W2118850452","https://openalex.org/W2120605154","https://openalex.org/W2123003832","https://openalex.org/W2147768505","https://openalex.org/W2152974894","https://openalex.org/W2158069733","https://openalex.org/W2165712214","https://openalex.org/W2175575774","https://openalex.org/W2290689761","https://openalex.org/W6676626839"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W3147024994","https://openalex.org/W2063246903","https://openalex.org/W2374055396","https://openalex.org/W1978302214","https://openalex.org/W2021817983","https://openalex.org/W3008559849","https://openalex.org/W2371177901"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,47,67,110,127],"phonetically-aware":[4,139,160],"joint":[5],"density":[6],"Gaussian":[7],"mixture":[8],"model":[9],"(JD-GMM)":[10],"framework":[11],"for":[12],"voice":[13],"conversion":[14,43,95],"that":[15,29,49,157],"no":[16],"longer":[17],"requires":[18],"parallel":[19],"data":[20],"from":[21,59,85,105],"source":[22,86],"speaker":[23,87,118],"at":[24,94],"the":[25,30,42,60,70,106,132,137,146,169,173],"training":[26,151,181],"stage.":[27,96],"Considering":[28],"phonetic":[31,52,82,98],"level":[32],"features":[33,54,57,76,84,93,100],"contain":[34],"text":[35],"information":[36],"which":[37],"should":[38],"be":[39,124],"preserved":[40],"in":[41,115,172],"task,":[44],"we":[45,79],"propose":[46],"method":[48,140,144,162],"only":[50,177],"concatenates":[51],"discriminant":[53,83,99],"and":[55],"spectral":[56,92],"extracted":[58,102],"same":[61],"target":[62,90,178],"speakers":[63],"speech":[64,179],"to":[65,88,168],"train":[66],"JD-GMM.":[68],"After":[69],"mapping":[71],"relationship":[72],"of":[73,109,131,175],"these":[74],"two":[75],"is":[77],"trained,":[78],"can":[80,123,163],"use":[81],"estimate":[89],"speaker's":[91],"The":[97,153],"are":[101],"using":[103,176],"PCA":[104],"output":[107],"layer":[108],"deep":[111],"neural":[112],"network":[113],"(DNN)":[114],"an":[116],"automatic":[117],"recognition":[119],"(ASR)":[120],"system.":[121],"It":[122],"seen":[125],"as":[126,180],"low":[128],"dimensional":[129],"representation":[130],"senone":[133],"posteriors.":[134],"We":[135],"compare":[136],"proposed":[138,159],"with":[141],"conventional":[142,170],"JD-GMM":[143,171],"on":[145],"Voice":[147],"Conversion":[148],"Challenge":[149],"2016":[150],"database.":[152],"experimental":[154],"results":[155],"show":[156],"our":[158],"feature":[161],"obtain":[164],"similar":[165],"performance":[166],"compared":[167],"case":[174],"data.":[182]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}