{"id":"https://openalex.org/W2156194831","doi":"https://doi.org/10.1109/icassp.2011.5947373","title":"High accurate model-integration-based voice conversion using dynamic features and model structure optimization","display_name":"High accurate model-integration-based voice conversion using dynamic features and model structure optimization","publication_year":2011,"publication_date":"2011-05-01","ids":{"openalex":"https://openalex.org/W2156194831","doi":"https://doi.org/10.1109/icassp.2011.5947373","mag":"2156194831"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2011.5947373","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2011.5947373","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5010841595","display_name":"Daisuke Saito","orcid":"https://orcid.org/0000-0003-3200-579X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Daisuke Saito","raw_affiliation_strings":["University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001291873","display_name":"Shinji Watanabe","orcid":"https://orcid.org/0000-0002-5970-8631"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shinji Watanabe","raw_affiliation_strings":["NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018620798","display_name":"Atsushi Nakamura","orcid":"https://orcid.org/0000-0003-0788-2221"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Atsushi Nakamura","raw_affiliation_strings":["NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041213266","display_name":"Nobuaki Minematsu","orcid":"https://orcid.org/0000-0002-8778-9555"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nobuaki Minematsu","raw_affiliation_strings":["University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5010841595"],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":0.4402,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74986629,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"4576","last_page":"4579"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9883000254631042,"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":0.7545191645622253},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6528803110122681},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5133928060531616},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5015215873718262},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4513895809650421},{"id":"https://openalex.org/keywords/gaussian-network-model","display_name":"Gaussian network model","score":0.4187087416648865},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41806313395500183},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.41364994645118713},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3725301921367645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33902066946029663},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08928373456001282}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7545191645622253},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6528803110122681},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5133928060531616},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5015215873718262},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4513895809650421},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.4187087416648865},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41806313395500183},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.41364994645118713},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3725301921367645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33902066946029663},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08928373456001282},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp.2011.5947373","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2011.5947373","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.378.353","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.378.353","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.gavo.t.u-tokyo.ac.jp/~mine/paper/PDF/2011/ICASSP_p4576-4579_t2011-5.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W17772838","https://openalex.org/W33533989","https://openalex.org/W49412823","https://openalex.org/W102093577","https://openalex.org/W193510348","https://openalex.org/W1935012542","https://openalex.org/W1965255698","https://openalex.org/W2049686551","https://openalex.org/W2120605154","https://openalex.org/W2123003832","https://openalex.org/W2126143605","https://openalex.org/W2153057929","https://openalex.org/W2156142001","https://openalex.org/W2167270514","https://openalex.org/W4285719527","https://openalex.org/W6602007935"],"related_works":["https://openalex.org/W1578916557","https://openalex.org/W4295035285","https://openalex.org/W2350507978","https://openalex.org/W2122170741","https://openalex.org/W2365475731","https://openalex.org/W2073372811","https://openalex.org/W2386291451","https://openalex.org/W2008969177","https://openalex.org/W3162483426","https://openalex.org/W292771262"],"abstract_inverted_index":{"This":[0],"paper":[1,91],"combines":[2],"a":[3,8,25,30,35,93],"parameter":[4,76,94],"generation":[5,95],"algorithm":[6,96],"and":[7,29,78,105,117,137],"model":[9,28,32,84,116,120,151],"optimization":[10],"approach":[11,131,140],"with":[12],"the":[13,38,54,62,64,67,72,75,79,83,88,102,113,118,122,129,133,138,143,149],"model-integration-based":[14],"voice":[15,42],"con":[16],"version":[17],"(MIVC).":[18],"We":[19],"have":[20],"proposed":[21],"probabilistic":[22],"integration":[23],"of":[24,37,66,135,146,148],"joint":[26,114],"density":[27,115],"speaker":[31,119,150],"to":[33,81],"mitigate":[34],"requirement":[36],"parallel":[39],"corpus":[40],"in":[41],"conversion":[43],"(VC)":[44],"based":[45],"on":[46],"Gaussian":[47],"Mixture":[48],"Model":[49],"(GMM).":[50],"As":[51],"well":[52],"as":[53],"other":[55],"VC":[56,136],"methods,":[57],"MIVC":[58],"also":[59],"suffers":[60],"from":[61],"problems;":[63],"degradation":[65],"perceptual":[68],"quality":[69],"caused":[70],"by":[71,98],"discontinuity":[73],"through":[74],"trajectory,":[77],"difficulty":[80],"optimize":[82],"structure.":[85],"To":[86],"solve":[87],"problems,":[89],"this":[90],"proposes":[92],"constrained":[97],"dynamic":[99],"features":[100],"for":[101,121,152],"first":[103,130],"problem":[104],"an":[106],"information":[107],"criterion":[108],"including":[109],"mutual":[110],"influences":[111],"between":[112],"second":[123,139],"problem.":[124],"Experimental":[125],"results":[126],"show":[127],"that":[128],"improved":[132],"performance":[134],"appropriately":[141],"predicted":[142],"optimal":[144],"number":[145],"mixtures":[147],"our":[153],"MIVC.":[154]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}