{"id":"https://openalex.org/W2921932556","doi":"https://doi.org/10.23919/apsipa.2018.8659541","title":"Speech Synthesis Using WaveNet Vocoder Based on Periodic/Aperiodic Decomposition","display_name":"Speech Synthesis Using WaveNet Vocoder Based on Periodic/Aperiodic Decomposition","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2921932556","doi":"https://doi.org/10.23919/apsipa.2018.8659541","mag":"2921932556"},"language":"en","primary_location":{"id":"doi:10.23919/apsipa.2018.8659541","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apsipa.2018.8659541","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5039729197","display_name":"Takato Fujimoto","orcid":null},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takato Fujimoto","raw_affiliation_strings":["Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101948311","display_name":"Takenori Yoshimura","orcid":"https://orcid.org/0000-0003-3964-5677"},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takenori Yoshimura","raw_affiliation_strings":["Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067594810","display_name":"Kei Hashimoto","orcid":"https://orcid.org/0000-0003-2081-0396"},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kei Hashimoto","raw_affiliation_strings":["Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049909008","display_name":"Keiichiro Oura","orcid":null},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keiichiro Oura","raw_affiliation_strings":["Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023240652","display_name":"Yoshihiko Nankaku","orcid":null},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshihiko Nankaku","raw_affiliation_strings":["Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan","institution_ids":["https://openalex.org/I197274945"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103023678","display_name":"Keiichi Tokuda","orcid":"https://orcid.org/0000-0001-6143-0133"},"institutions":[{"id":"https://openalex.org/I197274945","display_name":"Nagoya Institute of Technology","ror":"https://ror.org/055yf1005","country_code":"JP","type":"education","lineage":["https://openalex.org/I197274945"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keiichi Tokuda","raw_affiliation_strings":["Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Nagoya Institute of Technology, Nagoya, Japan","institution_ids":["https://openalex.org/I197274945"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5039729197"],"corresponding_institution_ids":["https://openalex.org/I197274945"],"apc_list":null,"apc_paid":null,"fwci":0.1629,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62187715,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"644","last_page":"648"},"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":0.9948999881744385,"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":0.9921000003814697,"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/aperiodic-graph","display_name":"Aperiodic graph","score":0.9771938920021057},{"id":"https://openalex.org/keywords/waveform","display_name":"Waveform","score":0.6517558693885803},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.6375430822372437},{"id":"https://openalex.org/keywords/speech-synthesis","display_name":"Speech synthesis","score":0.6343703269958496},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6272357106208801},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5792446732521057},{"id":"https://openalex.org/keywords/quasiperiodic-function","display_name":"Quasiperiodic function","score":0.472430557012558},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2207278609275818},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10428696870803833},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06435438990592957}],"concepts":[{"id":"https://openalex.org/C104247578","wikidata":"https://www.wikidata.org/wiki/Q4779368","display_name":"Aperiodic graph","level":2,"score":0.9771938920021057},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.6517558693885803},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6375430822372437},{"id":"https://openalex.org/C14999030","wikidata":"https://www.wikidata.org/wiki/Q16346","display_name":"Speech synthesis","level":2,"score":0.6343703269958496},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6272357106208801},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5792446732521057},{"id":"https://openalex.org/C55637507","wikidata":"https://www.wikidata.org/wiki/Q5870963","display_name":"Quasiperiodic function","level":2,"score":0.472430557012558},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2207278609275818},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10428696870803833},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06435438990592957},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/apsipa.2018.8659541","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apsipa.2018.8659541","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W68089216","https://openalex.org/W80543058","https://openalex.org/W1861150963","https://openalex.org/W2039800941","https://openalex.org/W2042946036","https://openalex.org/W2049686551","https://openalex.org/W2088432713","https://openalex.org/W2093450784","https://openalex.org/W2101053356","https://openalex.org/W2102003408","https://openalex.org/W2117418893","https://openalex.org/W2129142580","https://openalex.org/W2145892079","https://openalex.org/W2150658333","https://openalex.org/W2150906086","https://openalex.org/W2151890809","https://openalex.org/W2152905683","https://openalex.org/W2154920538","https://openalex.org/W2168523336","https://openalex.org/W2171449031","https://openalex.org/W2228674556","https://openalex.org/W2395578248","https://openalex.org/W2471520273","https://openalex.org/W2519091744","https://openalex.org/W2603450495","https://openalex.org/W2749651610","https://openalex.org/W2949382160","https://openalex.org/W4395961139","https://openalex.org/W6603264027","https://openalex.org/W6675380101","https://openalex.org/W6682918086","https://openalex.org/W6683091923","https://openalex.org/W6711777497","https://openalex.org/W6736003376","https://openalex.org/W6865319189"],"related_works":["https://openalex.org/W3112195757","https://openalex.org/W3206287350","https://openalex.org/W4391047362","https://openalex.org/W1983278479","https://openalex.org/W2612433111","https://openalex.org/W2313091694","https://openalex.org/W2091784138","https://openalex.org/W3039748499","https://openalex.org/W4391376478","https://openalex.org/W2039489009"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"speech":[3,22,51,59,77,94,127],"synthesis":[4,60,95],"using":[5,96],"a":[6,97,116,139],"WaveNet":[7,98,141],"vocoder":[8,99,142],"based":[9,61,100,120,143],"on":[10,62,101,121,144],"periodic/aperiodic":[11,63,102],"decomposition.":[12,103],"Normally,":[13],"quasiperiodic":[14],"and":[15,32,36,82,110,125,132],"aperiodic":[16,33,37,83,111,133],"components":[17,38,84,112,134],"are":[18,39,113,135],"contained":[19],"in":[20,47,158],"human":[21],"waveforms.":[23],"Therefore,":[24],"it":[25],"is":[26],"important":[27],"to":[28],"accurately":[29],"model":[30,119],"periodic":[31,81,109,131],"components.":[34],"Periodic":[35],"represented":[40],"as":[41],"the":[42,45,54,69,105,151,155,159,162],"ratios":[43],"of":[44,71,161],"energies":[46],"conventional":[48,156],"statistical":[49,57],"parametric":[50,58],"synthesis.":[52],"On":[53],"other":[55],"hand,":[56],"decomposition":[64],"has":[65,74],"been":[66,75],"proposed.":[67],"Although":[68],"effectiveness":[70],"this":[72,90],"approach":[73,153,157],"shown,":[76],"waveforms":[78,128],"considering":[79,129],"both":[80,130],"cannot":[85],"be":[86],"generated":[87,137],"directly.":[88],"In":[89,104],"paper,":[91],"we":[92],"propose":[93],"proposed":[106,152],"approach,":[107],"separated":[108],"modeled":[114],"by":[115,138],"single":[117,140],"acoustic":[118],"deep":[122],"neural":[123,145],"networks,":[124],"then":[126],"directly":[136],"networks.":[146],"Experimental":[147],"results":[148],"show":[149],"that":[150],"outperforms":[154],"naturalness":[160],"synthesized":[163],"speech.":[164]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}