{"id":"https://openalex.org/W2990699094","doi":"https://doi.org/10.1145/3364908.3365297","title":"Normalized Vowel Duration Enhanced RNN Prosodic Phrase Detection Model","display_name":"Normalized Vowel Duration Enhanced RNN Prosodic Phrase Detection Model","publication_year":2019,"publication_date":"2019-09-20","ids":{"openalex":"https://openalex.org/W2990699094","doi":"https://doi.org/10.1145/3364908.3365297","mag":"2990699094"},"language":"en","primary_location":{"id":"doi:10.1145/3364908.3365297","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3364908.3365297","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 International Symposium on Signal Processing Systems","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100301343","display_name":"Yizhi Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yizhi Wu","raw_affiliation_strings":["College of Information Science and Technology, Donghua University, China, Shanghai"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Donghua University, China, Shanghai","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455572","display_name":"Hongyan Li","orcid":"https://orcid.org/0000-0001-8819-904X"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyan Li","raw_affiliation_strings":["College of Information Science and Technology, Donghua University, China, Shanghai"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Donghua University, China, Shanghai","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056255679","display_name":"Sha Li","orcid":"https://orcid.org/0000-0001-6238-7544"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sha Li","raw_affiliation_strings":["College of Information Science and Technology, Donghua University, China, Shanghai"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Donghua University, China, Shanghai","institution_ids":["https://openalex.org/I181326427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181326427"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"154","last_page":"158"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9988999962806702,"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":0.9988999962806702,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9980000257492065,"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/T10403","display_name":"Phonetics and Phonology Research","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/duration","display_name":"Duration (music)","score":0.8266254663467407},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.7896535992622375},{"id":"https://openalex.org/keywords/vowel","display_name":"Vowel","score":0.7528517842292786},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7197704315185547},{"id":"https://openalex.org/keywords/prosody","display_name":"Prosody","score":0.6898159980773926},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6844199895858765},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6176918745040894},{"id":"https://openalex.org/keywords/intonation","display_name":"Intonation (linguistics)","score":0.6000519394874573},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5443408489227295},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5205484628677368},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4998292922973633},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3829379677772522},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20881900191307068},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1607566475868225},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.14289918541908264},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.06293752789497375}],"concepts":[{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.8266254663467407},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.7896535992622375},{"id":"https://openalex.org/C2779581591","wikidata":"https://www.wikidata.org/wiki/Q36244","display_name":"Vowel","level":2,"score":0.7528517842292786},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7197704315185547},{"id":"https://openalex.org/C542774811","wikidata":"https://www.wikidata.org/wiki/Q10880526","display_name":"Prosody","level":2,"score":0.6898159980773926},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6844199895858765},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6176918745040894},{"id":"https://openalex.org/C2781045179","wikidata":"https://www.wikidata.org/wiki/Q5576720","display_name":"Intonation (linguistics)","level":2,"score":0.6000519394874573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5443408489227295},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5205484628677368},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4998292922973633},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3829379677772522},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20881900191307068},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1607566475868225},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.14289918541908264},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.06293752789497375},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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:10.1145/3364908.3365297","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3364908.3365297","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 International Symposium on Signal Processing Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W37913285","https://openalex.org/W148837181","https://openalex.org/W1270504662","https://openalex.org/W1483979448","https://openalex.org/W1927421023","https://openalex.org/W1988000972","https://openalex.org/W1991148915","https://openalex.org/W1993347555","https://openalex.org/W1996430422","https://openalex.org/W2018172569","https://openalex.org/W2049075765","https://openalex.org/W2125689567","https://openalex.org/W2159372275","https://openalex.org/W2166820052","https://openalex.org/W2317392553","https://openalex.org/W2395417994","https://openalex.org/W2398044918","https://openalex.org/W2398538797","https://openalex.org/W4243020849"],"related_works":["https://openalex.org/W2382821289","https://openalex.org/W2800990999","https://openalex.org/W2355553914","https://openalex.org/W2554525739","https://openalex.org/W149862513","https://openalex.org/W1965454423","https://openalex.org/W2028501571","https://openalex.org/W2052542215","https://openalex.org/W2036564641","https://openalex.org/W2535580602"],"abstract_inverted_index":{"The":[0,40],"automatic":[1],"detection":[2,18,38,51,70,113],"of":[3,10,13,19,32,57,61,69,101,104,112,115,135],"intonation":[4],"phrases":[5,21,106,117,120],"is":[6,107],"an":[7],"important":[8],"part":[9],"the":[11,17,29,33,55,59,62,67,79,93,96,110,133],"study":[12],"prosody.":[14],"Features":[15],"for":[16,77,84],"prosodic":[20,49,105],"are":[22,124],"often":[23],"extracted":[24],"at":[25],"word-level":[26],"that":[27,92],"ignore":[28],"internal":[30],"structure":[31],"word,":[34],"resulting":[35],"in":[36,86,95],"low":[37],"accuracy.":[39],"present":[41],"paper":[42],"describes":[43],"a":[44,74],"recurrent":[45],"neural":[46],"network":[47],"(RNN)":[48],"phrase":[50],"model":[52],"developed":[53],"with":[54],"purpose":[56],"exploring":[58],"influence":[60],"normalized":[63,80,98,136],"vowel":[64,99,137],"duration":[65,81,100],"on":[66,122],"performance":[68],"model,":[71],"and":[72,109,118,128],"introduces":[73],"scale":[75],"factor":[76],"compensating":[78],"to":[82],"account":[83],"variations":[85],"speaking":[87],"rate.":[88],"Experimental":[89],"results":[90,114],"show":[91],"difference":[94],"average":[97],"different":[102],"levels":[103],"evident,":[108],"F-scores":[111],"intonational":[116],"intermediate":[119],"based":[121],"RNN":[123],"increased":[125],"by":[126],"2.8%":[127],"4.9%":[129],"respectively":[130],"after":[131],"adding":[132],"feature":[134],"duration.":[138]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}