{"id":"https://openalex.org/W2406091904","doi":"https://doi.org/10.21437/interspeech.2014-183","title":"A hierarchical viterbi algorithm for Mandarin hybrid speech synthesis system","display_name":"A hierarchical viterbi algorithm for Mandarin hybrid speech synthesis system","publication_year":2014,"publication_date":"2014-09-14","ids":{"openalex":"https://openalex.org/W2406091904","doi":"https://doi.org/10.21437/interspeech.2014-183","mag":"2406091904"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2014-183","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2014-183","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2014","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/A5075371310","display_name":"Ran Zhang","orcid":"https://orcid.org/0000-0002-3808-281X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ran Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111856667","display_name":"Zhengqi Wen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhengqi Wen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112613657","display_name":"Jianhua Tao","orcid":"https://orcid.org/0000-0002-9344-6428"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianhua Tao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100343662","display_name":"Ya Li","orcid":"https://orcid.org/0000-0002-6284-5039"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ya Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109831307","display_name":"Bing Liu","orcid":"https://orcid.org/0000-0003-2029-5187"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bing Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5015874035","display_name":"Xiaoyan Lou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaoyan Lou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"795","last_page":"799"},"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":0.996399998664856,"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/T12031","display_name":"Speech and dialogue systems","score":0.989799976348877,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/naturalness","display_name":"Naturalness","score":0.8426636457443237},{"id":"https://openalex.org/keywords/viterbi-algorithm","display_name":"Viterbi algorithm","score":0.8262436389923096},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8108816146850586},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7068878412246704},{"id":"https://openalex.org/keywords/speech-synthesis","display_name":"Speech synthesis","score":0.6366970539093018},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6114934086799622},{"id":"https://openalex.org/keywords/mandarin-chinese","display_name":"Mandarin Chinese","score":0.5498613119125366},{"id":"https://openalex.org/keywords/soft-output-viterbi-algorithm","display_name":"Soft output Viterbi algorithm","score":0.5041700601577759},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44403311610221863},{"id":"https://openalex.org/keywords/iterative-viterbi-decoding","display_name":"Iterative Viterbi decoding","score":0.4208306074142456},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.419948548078537},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34836429357528687},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.14660385251045227}],"concepts":[{"id":"https://openalex.org/C134537474","wikidata":"https://www.wikidata.org/wiki/Q17144832","display_name":"Naturalness","level":2,"score":0.8426636457443237},{"id":"https://openalex.org/C60582962","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Viterbi algorithm","level":3,"score":0.8262436389923096},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8108816146850586},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7068878412246704},{"id":"https://openalex.org/C14999030","wikidata":"https://www.wikidata.org/wiki/Q16346","display_name":"Speech synthesis","level":2,"score":0.6366970539093018},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6114934086799622},{"id":"https://openalex.org/C138954614","wikidata":"https://www.wikidata.org/wiki/Q9192","display_name":"Mandarin Chinese","level":2,"score":0.5498613119125366},{"id":"https://openalex.org/C130319729","wikidata":"https://www.wikidata.org/wiki/Q83886","display_name":"Soft output Viterbi algorithm","level":5,"score":0.5041700601577759},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44403311610221863},{"id":"https://openalex.org/C113638808","wikidata":"https://www.wikidata.org/wiki/Q6094410","display_name":"Iterative Viterbi decoding","level":5,"score":0.4208306074142456},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.419948548078537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34836429357528687},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.14660385251045227},{"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},{"id":"https://openalex.org/C157125643","wikidata":"https://www.wikidata.org/wiki/Q884707","display_name":"Block code","level":3,"score":0.0},{"id":"https://openalex.org/C193969084","wikidata":"https://www.wikidata.org/wiki/Q7452500","display_name":"Sequential decoding","level":4,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2014-183","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2014-183","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2014","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.5}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W18378689","https://openalex.org/W22981672","https://openalex.org/W262524825","https://openalex.org/W564913581","https://openalex.org/W1973766695","https://openalex.org/W1991133427","https://openalex.org/W2024189867","https://openalex.org/W2129142580","https://openalex.org/W2150658333","https://openalex.org/W2159528802","https://openalex.org/W2166823384","https://openalex.org/W2291159692"],"related_works":["https://openalex.org/W1915619113","https://openalex.org/W2143297499","https://openalex.org/W2767243160","https://openalex.org/W2386939465","https://openalex.org/W2993094530","https://openalex.org/W2062804535","https://openalex.org/W2544568790","https://openalex.org/W1879414379","https://openalex.org/W2073817053","https://openalex.org/W3096277017"],"abstract_inverted_index":{"The":[0],"hybrid":[1,186],"speech":[2,82,203],"synthesis":[3,189],"system,":[4],"which":[5,152],"combines":[6],"the":[7,43,64,73,76,90,94,121,125,128,132,138,141,176,184,192,200],"\r\n\thidden":[9],"Markov":[10],"model":[11],"and":[12,42,162,202],"unit":[13],"selection":[14],"method,":[15],"has":[16,167],"become":[17],"\r\n\tan":[19],"additional":[20],"main":[21],"stream":[22],"in":[23,98,124,183,198],"state-of-the-art":[24],"TTS":[25],"systems.":[26],"\r\n\tHowever,":[28],"traditional":[29,195],"Viterbi":[30,108,116,181],"algorithm":[31,109,182],"is":[32,85,119,130,153],"based":[33],"on":[34],"global":[35],"\r\n\tminimization":[37],"of":[38,75,78,93,115,165,194,205],"a":[39,106,150,168],"cost":[40],"function":[41],"procedure":[44],"can":[45,59],"end":[46],"up":[47],"\r\n\tselecting":[49],"some":[50],"poor-quality":[51],"units":[52],"with":[53],"larger":[54],"local":[55],"errors,":[56],"\r\n\twhich":[58,111],"hardly":[60],"be":[61],"tolerated":[62],"by":[63,155],"listeners.":[65],"In":[66,140],"Mandarin":[67,185],"\r\n\tand":[69],"many":[70],"other":[71,129],"languages,":[72],"naturalness":[74,201],"region":[77,151],"\r\n\tconsecutive":[80],"voiced":[81,160],"segments":[83],"(CVS)":[84],"more":[86],"essential":[87],"\r\n\tto":[89],"overall":[91],"quality":[92,204],"synthetic":[95],"speech.":[96,208],"Consequently,":[97],"\r\n\tthis":[100],"paper,":[101],"we":[102],"proposed":[103,142],"to":[104],"use":[105,177,193],"hierarchical":[107,180],"involves":[112],"two":[113,156],"rounds":[114],"search:":[117],"one":[118],"for":[120,131],"\r\n\tsub-paths":[123],"CVS":[126,147],"regions;":[127],"utterance":[133],"\r\n\tpath":[135],"connecting":[136],"all":[137],"sub-paths.":[139],"technique,":[143],"\r\n\twe":[145],"defined":[146],"Region":[148],"as":[149],"formed":[154],"or":[157],"\r\n\tmore":[159],"phones,":[161],"whose":[163],"observation":[164],"pitch":[166],"\r\n\tcontinuous":[170],"value.":[171],"Subjective":[172],"evaluations":[173],"suggest":[174],"that":[175],"\r\n\tof":[179],"\r\n\tspeech":[188],"system":[190],"outperforms":[191],"\r\n\talgorithm":[197],"both":[199],"\r\n\tsynthetic":[207]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}