{"id":"https://openalex.org/W1525071400","doi":"https://doi.org/10.21437/interspeech.2004-290","title":"Evaluation of corpus based tone prediction in mismatched environments for greek tts synthesis","display_name":"Evaluation of corpus based tone prediction in mismatched environments for greek tts synthesis","publication_year":2004,"publication_date":"2004-10-04","ids":{"openalex":"https://openalex.org/W1525071400","doi":"https://doi.org/10.21437/interspeech.2004-290","mag":"1525071400"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2004-290","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2004-290","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2004","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/A5091820192","display_name":"Panagiotis Zervas","orcid":"https://orcid.org/0000-0002-6531-4022"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Panagiotis Zervas","raw_affiliation_strings":["University of Patras;"],"affiliations":[{"raw_affiliation_string":"University of Patras;","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108443941","display_name":"Nikos Fakotakis","orcid":null},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Nikos Fakotakis","raw_affiliation_strings":["University of Patras;"],"affiliations":[{"raw_affiliation_string":"University of Patras;","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109187402","display_name":"George Kokkinakis","orcid":null},"institutions":[{"id":"https://openalex.org/I200777214","display_name":"National and Kapodistrian University of Athens","ror":"https://ror.org/04gnjpq42","country_code":"GR","type":"education","lineage":["https://openalex.org/I200777214"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"George Kokkinakis","raw_affiliation_strings":["National and kapodistrian University of Athens"],"affiliations":[{"raw_affiliation_string":"National and kapodistrian University of Athens","institution_ids":["https://openalex.org/I200777214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104090306","display_name":"George Kouroupetroglou","orcid":null},"institutions":[{"id":"https://openalex.org/I200777214","display_name":"National and Kapodistrian University of Athens","ror":"https://ror.org/04gnjpq42","country_code":"GR","type":"education","lineage":["https://openalex.org/I200777214"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"George Kouroupetroglou","raw_affiliation_strings":["National and kapodistrian University of Athens"],"affiliations":[{"raw_affiliation_string":"National and kapodistrian University of Athens","institution_ids":["https://openalex.org/I200777214"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004819616","display_name":"Gerasimos Xydas","orcid":"https://orcid.org/0009-0003-7817-5791"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Gerasimos Xydas","raw_affiliation_strings":["University of Patras;"],"affiliations":[{"raw_affiliation_string":"University of Patras;","institution_ids":["https://openalex.org/I174878644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5091820192"],"corresponding_institution_ids":["https://openalex.org/I174878644"],"apc_list":null,"apc_paid":null,"fwci":0.4625,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.73839204,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"761","last_page":"764"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998000264167786,"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":0.9998000264167786,"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/T11309","display_name":"Music and Audio Processing","score":0.9994999766349792,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9990000128746033,"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/computer-science","display_name":"Computer science","score":0.7994693517684937},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6216331124305725},{"id":"https://openalex.org/keywords/speech-synthesis","display_name":"Speech synthesis","score":0.5824177265167236},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5518175959587097},{"id":"https://openalex.org/keywords/tone","display_name":"Tone (literature)","score":0.522473931312561},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5067129731178284},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4411044418811798},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3970303237438202},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.38462793827056885},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06937375664710999}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7994693517684937},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6216331124305725},{"id":"https://openalex.org/C14999030","wikidata":"https://www.wikidata.org/wiki/Q16346","display_name":"Speech synthesis","level":2,"score":0.5824177265167236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5518175959587097},{"id":"https://openalex.org/C2780583480","wikidata":"https://www.wikidata.org/wiki/Q1366327","display_name":"Tone (literature)","level":2,"score":0.522473931312561},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5067129731178284},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4411044418811798},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3970303237438202},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38462793827056885},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06937375664710999},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.21437/interspeech.2004-290","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2004-290","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2004","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.74.213","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.74.213","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cgi.di.uoa.gr/~gxydas/publications/zervas_icslp2004.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.81.9031","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.81.9031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://speech.di.uoa.gr/sppages/spppdf/ICSLP2004-b.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W35180317","https://openalex.org/W89704689","https://openalex.org/W92308982","https://openalex.org/W125088710","https://openalex.org/W141255067","https://openalex.org/W204924188","https://openalex.org/W1479882947","https://openalex.org/W1500192039","https://openalex.org/W1543527380","https://openalex.org/W1594031697","https://openalex.org/W1604793456","https://openalex.org/W2093476462","https://openalex.org/W2124924501","https://openalex.org/W3085162807"],"related_works":["https://openalex.org/W2372714829","https://openalex.org/W2087509987","https://openalex.org/W2273760643","https://openalex.org/W2564078509","https://openalex.org/W2603461750","https://openalex.org/W2383107393","https://openalex.org/W2388666590","https://openalex.org/W2353792789","https://openalex.org/W2363183509","https://openalex.org/W2370832642"],"abstract_inverted_index":{"One":[0],"of":[1,13,24,78,123],"the":[2,10,22,32,58,69,76,79,98,113,121],"main":[3],"aspects":[4],"in":[5,27,103,109],"Text-to-Speech":[6],"(TtS)":[7],"synthesis":[8],"is":[9],"successful":[11],"prediction":[12],"tonal":[14],"events.":[15],"In":[16],"this":[17],"work":[18],"we":[19,67,81],"deal":[20],"with":[21],"evaluation":[23],"corpus-based":[25],"models":[26,101,115],"operational":[28],"environments":[29],"other":[30],"than":[31],"training":[33],"ones.":[34],"Two":[35],"pitch":[36],"accent":[37],"frameworks":[38],"derived":[39],"by":[40,56],"linguistically":[41],"enriched":[42],"speech":[43],"data":[44,72],"from":[45],"a":[46,50,64,117],"generic":[47,114],"domain":[48,52,100,122],"and":[49,91],"limited":[51,99],"were":[53],"initially":[54],"evaluated":[55],"applying":[57],"10-fold":[59],"cross":[60,70],"validation":[61],"method.":[62],"As":[63],"second":[65],"step,":[66],"utilized":[68],"domains":[71],"validation.":[73],"Due":[74],"to":[75],"heterogeneity":[77],"data,":[80],"further":[82],"employed":[83],"three":[84],"machine":[85],"learning":[86],"approaches,":[87],"CART,":[88],"Naive":[89],"Bayes":[90],"Bayesian":[92],"networks.":[93],"The":[94],"results":[95],"demonstrate":[96],"that":[97],"achieve":[102],"average":[104],"10":[105],"%":[106],"improved":[107],"accuracy":[108],"self-domain":[110],"evaluation,":[111],"while":[112],"preserve":[116],"their":[118],"performance":[119],"regardless":[120],"application.":[124],"1.":[125]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}