{"id":"https://openalex.org/W2787378487","doi":"https://doi.org/10.1109/apsipa.2017.8282282","title":"Emotional statistical parametric speech synthesis using LSTM-RNNs","display_name":"Emotional statistical parametric speech synthesis using LSTM-RNNs","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2787378487","doi":"https://doi.org/10.1109/apsipa.2017.8282282","mag":"2787378487"},"language":"en","primary_location":{"id":"doi:10.1109/apsipa.2017.8282282","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2017.8282282","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5046787619","display_name":"Shumin An","orcid":"https://orcid.org/0000-0002-0419-9278"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shumin An","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059767940","display_name":"Zhen-Hua Ling","orcid":"https://orcid.org/0000-0001-7853-5273"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Ling","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057227915","display_name":"Li-Rong Dai","orcid":"https://orcid.org/0000-0002-0859-2827"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lirong Dai","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046787619"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":4.8755,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.96156317,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1613","last_page":"1616"},"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":0.9957000017166138,"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":0.9951000213623047,"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":0.7731627225875854},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6601218581199646},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6429862976074219},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5891059041023254},{"id":"https://openalex.org/keywords/speech-synthesis","display_name":"Speech synthesis","score":0.5654304623603821},{"id":"https://openalex.org/keywords/sadness","display_name":"Sadness","score":0.5637086629867554},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.469735711812973},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44999751448631287},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.44150933623313904},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4265539348125458},{"id":"https://openalex.org/keywords/naturalness","display_name":"Naturalness","score":0.41574689745903015},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.34717217087745667},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3103487491607666},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.08654800057411194}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7731627225875854},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6601218581199646},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6429862976074219},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5891059041023254},{"id":"https://openalex.org/C14999030","wikidata":"https://www.wikidata.org/wiki/Q16346","display_name":"Speech synthesis","level":2,"score":0.5654304623603821},{"id":"https://openalex.org/C2779812673","wikidata":"https://www.wikidata.org/wiki/Q169251","display_name":"Sadness","level":3,"score":0.5637086629867554},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.469735711812973},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44999751448631287},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.44150933623313904},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4265539348125458},{"id":"https://openalex.org/C134537474","wikidata":"https://www.wikidata.org/wiki/Q17144832","display_name":"Naturalness","level":2,"score":0.41574689745903015},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.34717217087745667},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3103487491607666},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08654800057411194},{"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/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipa.2017.8282282","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2017.8282282","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W68089216","https://openalex.org/W1613141907","https://openalex.org/W1886418050","https://openalex.org/W2039800941","https://openalex.org/W2042360461","https://openalex.org/W2085013480","https://openalex.org/W2087110403","https://openalex.org/W2102146461","https://openalex.org/W2117418893","https://openalex.org/W2129142580","https://openalex.org/W2149425161","https://openalex.org/W2170849167","https://openalex.org/W2294797155","https://openalex.org/W2399843513","https://openalex.org/W2516321201","https://openalex.org/W2605320104","https://openalex.org/W4235154690","https://openalex.org/W6602768981","https://openalex.org/W6685045429","https://openalex.org/W6696843773","https://openalex.org/W6736204136"],"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/W4388134110","https://openalex.org/W2535215250","https://openalex.org/W1813881148"],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"the":[3,42,62,71,76,87,97,107,123,168,173,180,189,194,202,215,218],"methods":[4],"for":[5,52,81,185],"emotional":[6,133],"statistical":[7],"parametric":[8],"speech":[9,63,82,85,134,157,209],"synthesis":[10,135],"(SPSS)":[11],"using":[12,61,96],"recurrent":[13],"neural":[14],"networks":[15],"(RNN)":[16],"with":[17,32,137],"long":[18],"short-term":[19],"memory":[20],"(LSTM)":[21],"units.":[22],"Two":[23],"modeling":[24,28,31,165,170,176,196],"approaches,":[25],"i.e.,":[26],"emotion-dependent":[27,72,164,175],"and":[29,37,84,145,172,205,213],"unified":[30,92,108,169,195],"emotion":[33,54,104,112,124,139,182,190,203],"codes,":[34],"are":[35,49,198],"implemented":[36],"compared":[38],"by":[39,75,193,211],"experiments.":[40],"In":[41,106],"first":[43],"approach,":[44],"LSTM-RNN-":[45],"based":[46],"acoustic":[47,58,94],"models":[48],"built":[50],"separately":[51],"each":[53],"type.":[55],"A":[56],"speaker-independent":[57],"model":[59,95,119],"estimated":[60],"data":[64,99],"from":[65],"multi-speakers":[66],"is":[67,115],"adopted":[68],"to":[69,117,121],"initialize":[70],"LSTM-RNNS.":[73],"Inspired":[74],"speaker":[77],"code":[78,113],"techniques":[79],"developed":[80],"recognition":[83],"synthesis,":[86],"second":[88],"approach":[89,166,171,197],"builds":[90],"a":[91,101],"LSTM-RNN-based":[93],"training":[98,219],"of":[100,103,126,155,179,200,207],"variety":[102],"types.":[105],"LSTM-RNN":[109],"model,":[110],"an":[111,132],"vector":[114],"input":[116],"all":[118],"layers":[120],"indicate":[122],"characteristics":[125],"current":[127],"utterance.":[128],"Experimental":[129],"results":[130],"on":[131],"database":[136],"four":[138],"types":[140],"(neutral":[141],"style,":[142],"happiness,":[143],"anger,":[144],"sadness)":[146],"show":[147],"that":[148],"both":[149],"approaches":[150],"achieve":[151],"significant":[152],"better":[153],"naturalness":[154],"synthetic":[156,186,208],"than":[158],"HMM-based":[159,174],"emotion-":[160],"dependent":[161],"modeling.":[162],"The":[163],"outperforms":[167],"in":[177,217],"terms":[178],"subjective":[181],"classification":[183],"rates":[184],"speech.":[187],"Furthermore,":[188],"codes":[191,216],"used":[192],"capable":[199],"controlling":[201],"type":[204],"intensity":[206],"effectively":[210],"interpolating":[212],"extrapolating":[214],"set.":[220]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
