{"id":"https://openalex.org/W1587861045","doi":"https://doi.org/10.21437/interspeech.2010-179","title":"Improved training of excitation for HMM-based parametric speech synthesis","display_name":"Improved training of excitation for HMM-based parametric speech synthesis","publication_year":2010,"publication_date":"2010-09-26","ids":{"openalex":"https://openalex.org/W1587861045","doi":"https://doi.org/10.21437/interspeech.2010-179","mag":"1587861045"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2010-179","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2010-179","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2010","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://naist.repo.nii.ac.jp/records/4740","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109350986","display_name":"Yoshinori Shiga","orcid":null},"institutions":[{"id":"https://openalex.org/I90023481","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349","country_code":"JP","type":"facility","lineage":["https://openalex.org/I90023481"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yoshinori Shiga","raw_affiliation_strings":["National Institute of Information and Communications Technology"],"affiliations":[{"raw_affiliation_string":"National Institute of Information and Communications Technology","institution_ids":["https://openalex.org/I90023481"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078330211","display_name":"Tomoki Toda","orcid":"https://orcid.org/0000-0001-8146-1279"},"institutions":[{"id":"https://openalex.org/I75917431","display_name":"Nara Institute of Science and Technology","ror":"https://ror.org/05bhada84","country_code":"JP","type":"education","lineage":["https://openalex.org/I75917431"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoki Toda","raw_affiliation_strings":["Nara Institute of Science and Technology, Ikoma, Japan"],"affiliations":[{"raw_affiliation_string":"Nara Institute of Science and Technology, Ikoma, Japan","institution_ids":["https://openalex.org/I75917431"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110763152","display_name":"Shinsuke Sakai","orcid":null},"institutions":[{"id":"https://openalex.org/I90023481","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349","country_code":"JP","type":"facility","lineage":["https://openalex.org/I90023481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shinsuke Sakai","raw_affiliation_strings":["National Institute of Information and Communications Technology, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Information and Communications Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I90023481"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114514387","display_name":"Hisashi Kawai","orcid":"https://orcid.org/0000-0002-0914-5092"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hisashi Kawai","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5109350986"],"corresponding_institution_ids":["https://openalex.org/I90023481"],"apc_list":null,"apc_paid":null,"fwci":0.929,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.79394292,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"809","last_page":"812"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":1.0,"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":1.0,"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":0.9991000294685364,"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":0.9976999759674072,"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/hidden-markov-model","display_name":"Hidden Markov model","score":0.819747269153595},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.7286872267723083},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.6616156697273254},{"id":"https://openalex.org/keywords/speech-synthesis","display_name":"Speech synthesis","score":0.6260150074958801},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.610295832157135},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5720449090003967},{"id":"https://openalex.org/keywords/association","display_name":"Association (psychology)","score":0.45813870429992676},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3537425398826599},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.14115247130393982},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12142911553382874},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11666566133499146},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06929430365562439}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.819747269153595},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.7286872267723083},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6616156697273254},{"id":"https://openalex.org/C14999030","wikidata":"https://www.wikidata.org/wiki/Q16346","display_name":"Speech synthesis","level":2,"score":0.6260150074958801},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.610295832157135},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5720449090003967},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.45813870429992676},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3537425398826599},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.14115247130393982},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12142911553382874},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11666566133499146},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06929430365562439},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.21437/interspeech.2010-179","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2010-179","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2010","raw_type":"proceedings-article"},{"id":"pmh:oai:irdb.nii.ac.jp:01146:0005783191","is_oa":true,"landing_page_url":"https://naist.repo.nii.ac.jp/records/4740","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":{"id":"pmh:oai:irdb.nii.ac.jp:01146:0005783191","is_oa":true,"landing_page_url":"https://naist.repo.nii.ac.jp/records/4740","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W95551363","https://openalex.org/W155946340","https://openalex.org/W163616957","https://openalex.org/W1514941256","https://openalex.org/W1589634022","https://openalex.org/W1600722501","https://openalex.org/W1756939916","https://openalex.org/W2042691334","https://openalex.org/W2049686551","https://openalex.org/W2093450784","https://openalex.org/W2132119275","https://openalex.org/W2143490509","https://openalex.org/W2286166914","https://openalex.org/W2395578248","https://openalex.org/W2500358397"],"related_works":["https://openalex.org/W2053269318","https://openalex.org/W2364370872","https://openalex.org/W2025614924","https://openalex.org/W2294335174","https://openalex.org/W2097963413","https://openalex.org/W3145575561","https://openalex.org/W2001275470","https://openalex.org/W2904846757","https://openalex.org/W175280642","https://openalex.org/W2688184458"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"an":[3,14],"improved":[4,96],"method":[5],"of":[6,20,41,103],"training":[7,85],"for":[8,82],"the":[9,18,33,38,42,53,57,63,65,74,93,95,100,107,117,130,139,143],"unvoiced":[10,34,66,83,111,125],"filter":[11,35,67,84,112,126],"that":[12,89,124],"comprises":[13],"excitation":[15,46,59],"model,":[16],"within":[17],"framework":[19],"parametric":[21],"speech":[22,76],"synthesis":[23],"based":[24],"on":[25],"hidden":[26],"Markov":[27],"models.":[28],"The":[29,48,110],"conventional":[30,144],"approach":[31,97,132],"calculates":[32],"response":[36],"from":[37,92,106,116],"differential":[39,49],"signal":[40,105],"residual":[43,104],"and":[44],"voiced":[45,58],"estimate.":[47],"signal,":[50],"however,":[51],"includes":[52],"error":[54],"generated":[55],"by":[56,62],"estimates.":[60],"Contaminated":[61],"error,":[64],"tends":[68],"to":[69,77,86,138],"be":[70,78],"overestimated,":[71],"which":[72],"causes":[73],"synthetic":[75],"noisy.":[79],"In":[80],"order":[81],"obtain":[87],"targets":[88],"are":[90,133],"free":[91],"contamination,":[94],"first":[98],"separates":[99],"non-periodic":[101,118],"component":[102,119],"periodic":[108],"component.":[109],"is":[113],"then":[114],"trained":[115,128,141],"signals.":[120],"Experimental":[121],"results":[122],"show":[123],"responses":[127,140],"with":[129,142],"new":[131],"clearly":[134],"noiseless,":[135],"in":[136],"contrast":[137],"approach.":[145]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
