{"id":"https://openalex.org/W179658191","doi":"https://doi.org/10.21437/interspeech.2010-77","title":"Automatic detection of abnormal stress patterns in unit selection synthesis","display_name":"Automatic detection of abnormal stress patterns in unit selection synthesis","publication_year":2010,"publication_date":"2010-09-26","ids":{"openalex":"https://openalex.org/W179658191","doi":"https://doi.org/10.21437/interspeech.2010-77","mag":"179658191"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2010-77","doi":"https://doi.org/10.21437/interspeech.2010-77","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2010-77","pdf_url":null,"source":{"id":"https://openalex.org/S4393918409","display_name":"Interspeech (USB)","issn_l":"2308-457X","issn":["2308-457X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2010","raw_type":"proceedings-article"},"volume":null,"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/A5066280625","display_name":"Yeon-Jun Kim","orcid":"https://orcid.org/0000-0003-4732-2501","observed_orcids":["https://orcid.org/0000-0003-4732-2501"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yeon-Jun Kim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5109546051","display_name":"Mark C. Beutnagel","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mark C. Beutnagel","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":0.5172,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56179205,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"170","last_page":"173"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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"}},"topics":[{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","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":0.0010000000474974513,"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"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.0003000000142492354,"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/unit-selection-speech-synthesis","display_name":"unit selection speech synthesis","score":0.7979999780654907},{"id":"https://openalex.org/keywords/lexical-stress","display_name":"word stress","score":0.9020000100135803},{"id":"https://openalex.org/keywords/acoustic-characteristics","display_name":"acoustic features","score":0.5839999914169312},{"id":"https://openalex.org/keywords/cart","display_name":"CART","score":0.6299999952316284},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.9639999866485596},{"id":"https://openalex.org/keywords/speech-synthesis","display_name":"speech synthesis","score":0.5609999895095825}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.634759783744812},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6109552383422852},{"id":"https://openalex.org/C122637931","wikidata":"https://www.wikidata.org/wiki/Q118084","display_name":"Unit (ring theory)","level":2,"score":0.47040849924087524},{"id":"https://openalex.org/C21036866","wikidata":"https://www.wikidata.org/wiki/Q181767","display_name":"Stress (linguistics)","level":2,"score":0.466778427362442},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3038191497325897},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11414662003517151},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.21437/interspeech.2010-77","doi":"https://doi.org/10.21437/interspeech.2010-77","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2010-77","pdf_url":null,"source":{"id":"https://openalex.org/S4393918409","display_name":"Interspeech (USB)","issn_l":"2308-457X","issn":["2308-457X"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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:CiteSeerX.psu:10.1.1.307.1403","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.307.1403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www2.research.att.com/~ttsweb/tts/papers/2010/is2010_stress.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W1992153276","https://openalex.org/W2055366115","https://openalex.org/W2134908224","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W228314209","https://openalex.org/W2405277863","https://openalex.org/W2148724232","https://openalex.org/W2068603351","https://openalex.org/W2740154306","https://openalex.org/W2399755580","https://openalex.org/W205537210","https://openalex.org/W2054222370","https://openalex.org/W2089073319","https://openalex.org/W7098297925"],"abstract_inverted_index":{"This":[0],"paper":[1],"introduces":[2],"a":[3,112],"method":[4],"to":[5,41,48,135],"detect":[6],"lexical":[7,145],"stress":[8,21,55,74,104,146],"errors":[9,50],"in":[10,33,101],"unit":[11,27,35,143],"selection":[12],"synthesis":[13,47],"automatically":[14],"using":[15],"machine":[16,61],"learning":[17,62],"algorithms.":[18],"If":[19],"unintended":[20],"patterns":[22],"can":[23],"be":[24,39],"detected":[25],"following":[26],"selection,":[28,144],"based":[29,128],"on":[30,129],"features":[31],"available":[32],"the":[34,43,87,102,136],"database,":[36],"it":[37],"may":[38],"possible":[40],"modify":[42],"units":[44],"during":[45],"waveform":[46],"correct":[49],"and":[51,72,78],"produce":[52],"an":[53],"acceptable":[54],"pattern.":[56],"In":[57],"this":[58],"paper,":[59],"three":[60],"algorithms":[63],"were":[64],"trained":[65],"with":[66],"acoustic":[67],"measurements":[68],"from":[69],"natural":[70,103],"utterances":[71],"corresponding":[73],"patterns:":[75],"CART,":[76],"SVM":[77],"MaxEnt.":[79],"Our":[80],"experimental":[81],"results":[82],"showed":[83],"that":[84,125],"MaxEnt":[85],"performs":[86],"best":[88],"(83.3":[89],"%":[90,95],"for":[91,96],"3-syllable":[92],"words,":[93],"88.7":[94],"4-syllable":[97],"words":[98],"correctly":[99],"classified)":[100],"pattern":[105],"classification.":[106],"Though":[107],"classification":[108],"rates":[109],"are":[110,118],"good,":[111],"large":[113],"number":[114],"of":[115],"false":[116,130],"alarms":[117],"produced.":[119],"However,":[120],"there":[121],"is":[122],"some":[123],"indication":[124],"signal":[126],"modifications":[127],"positives":[131],"do":[132],"little":[133],"harm":[134],"speech":[137,141],"output.":[138],"Index":[139],"Terms:":[140],"synthesis,":[142],"1.":[147]},"counts_by_year":[],"updated_date":"2026-10-06T10:28:23.643775","created_date":"2016-06-24T00:00:00"}
