{"id":"https://openalex.org/W3015446641","doi":"https://doi.org/10.1109/icassp40776.2020.9052935","title":"Utterance-Level Sequential Modeling for Deep Gaussian Process Based Speech Synthesis Using Simple Recurrent Unit","display_name":"Utterance-Level Sequential Modeling for Deep Gaussian Process Based Speech Synthesis Using Simple Recurrent Unit","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015446641","doi":"https://doi.org/10.1109/icassp40776.2020.9052935","mag":"3015446641"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9052935","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9052935","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 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/A5024181978","display_name":"Tomoki Koriyama","orcid":"https://orcid.org/0000-0002-8347-5604"},"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":"Tomoki Koriyama","raw_affiliation_strings":["Graduate School of Information Science and Technology, The University of Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, The University of Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003814223","display_name":"Hiroshi Saruwatari","orcid":"https://orcid.org/0000-0003-0876-5617"},"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":"Hiroshi Saruwatari","raw_affiliation_strings":["Graduate School of Information Science and Technology, The University of Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, The University of Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5024181978"],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":0.7954,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.77681309,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"14","issue":null,"first_page":"7249","last_page":"7253"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9976999759674072,"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":0.9976999759674072,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9976999759674072,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9718999862670898,"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":0.7837110757827759},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6370960474014282},{"id":"https://openalex.org/keywords/naturalness","display_name":"Naturalness","score":0.5193915963172913},{"id":"https://openalex.org/keywords/speech-synthesis","display_name":"Speech synthesis","score":0.5145596861839294},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4963555932044983},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4901038110256195},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4745267927646637},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.4661964476108551},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46076086163520813},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4523197412490845},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41238871216773987},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.31199365854263306},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1181098222732544}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7837110757827759},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6370960474014282},{"id":"https://openalex.org/C134537474","wikidata":"https://www.wikidata.org/wiki/Q17144832","display_name":"Naturalness","level":2,"score":0.5193915963172913},{"id":"https://openalex.org/C14999030","wikidata":"https://www.wikidata.org/wiki/Q16346","display_name":"Speech synthesis","level":2,"score":0.5145596861839294},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4963555932044983},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4901038110256195},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4745267927646637},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.4661964476108551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46076086163520813},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4523197412490845},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41238871216773987},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.31199365854263306},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1181098222732544},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9052935","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9052935","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6499999761581421,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1866206747","https://openalex.org/W1909320841","https://openalex.org/W1959608418","https://openalex.org/W2102003408","https://openalex.org/W2144902422","https://openalex.org/W2166851633","https://openalex.org/W2167608136","https://openalex.org/W2394662942","https://openalex.org/W2471520273","https://openalex.org/W2728139190","https://openalex.org/W2765486990","https://openalex.org/W2807037403","https://openalex.org/W2886022419","https://openalex.org/W2911315040","https://openalex.org/W2921135010","https://openalex.org/W2936539725","https://openalex.org/W2962875063","https://openalex.org/W2962897394","https://openalex.org/W2962897886","https://openalex.org/W2963074410","https://openalex.org/W2963174729","https://openalex.org/W2963609956","https://openalex.org/W2963711523","https://openalex.org/W2964121744","https://openalex.org/W2964243274","https://openalex.org/W2972956431","https://openalex.org/W4293459451","https://openalex.org/W4294562888","https://openalex.org/W4297813703","https://openalex.org/W6631190155","https://openalex.org/W6639216784","https://openalex.org/W6639732818","https://openalex.org/W6640963894","https://openalex.org/W6675380101","https://openalex.org/W6681302627","https://openalex.org/W6684578138","https://openalex.org/W6684918892","https://openalex.org/W6712239235","https://openalex.org/W6738492492","https://openalex.org/W6740718799","https://openalex.org/W6747594027"],"related_works":["https://openalex.org/W4391272374","https://openalex.org/W1914543332","https://openalex.org/W2946856121","https://openalex.org/W40885451","https://openalex.org/W2108985546","https://openalex.org/W2081919107","https://openalex.org/W2433276473","https://openalex.org/W1537411440","https://openalex.org/W2535215250","https://openalex.org/W2024201202"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,10,19,36,66,95,106],"deep":[4,21],"Gaussian":[5],"process":[6],"(DGP)":[7],"model":[8,22,32,39,103],"with":[9,28],"recurrent":[11,90,97,107],"architecture":[12,91],"for":[13,100],"speech":[14,55,115,137],"sequence":[15],"modeling.":[16],"DGP":[17,82,143],"is":[18,35],"Bayesian":[20],"that":[23,40,52,81,133],"can":[24,41,83,112],"be":[25,84],"trained":[26],"effectively":[27],"the":[29,46,53,71,101,120,134],"consideration":[30],"of":[31,73,124],"complexity":[33],"and":[34,128,149],"kernel":[37],"regression":[38],"have":[42],"high":[43,121],"expressibility.":[44],"In":[45],"previous":[47],"studies,":[48],"it":[49],"was":[50],"shown":[51],"DGP-based":[54],"synthesis":[56,138],"outperformed":[57],"neural":[58,154],"network-based":[59],"one,":[60],"in":[61,76,109],"which":[62,110],"both":[63],"models":[64],"used":[65],"feed-forward":[67,142],"architecture.":[68],"To":[69],"improve":[70],"naturalness":[72],"synthetic":[74],"speech,":[75],"this":[77],"paper,":[78],"we":[79,111],"show":[80,132],"applied":[85],"to":[86,104],"utterance-level":[87],"modeling":[88],"using":[89,119],"models.":[92],"We":[93],"adopt":[94],"simple":[96],"unit":[98],"(SRU)":[99],"proposed":[102,135],"achieve":[105],"architecture,":[108],"execute":[113],"fast":[114],"parameter":[116],"generation":[117],"by":[118],"parallelization":[122],"nature":[123],"SRU.":[125],"The":[126],"objective":[127],"subjective":[129],"evaluation":[130],"results":[131],"SRU-DGP-based":[136],"outperforms":[139],"not":[140],"only":[141],"but":[144],"also":[145],"automatically":[146],"tuned":[147],"SRU-":[148],"long":[150],"short-term":[151],"memory":[152],"(LSTM)-based":[153],"networks.":[155]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}