{"id":"https://openalex.org/W1993281691","doi":"https://doi.org/10.1002/(sici)1520-684x(200004)31:4<98::aid-scj10>3.0.co;2-j","title":"Discriminative state-dependent weightings of duration-based state transition model through minimum classification error training","display_name":"Discriminative state-dependent weightings of duration-based state transition model through minimum classification error training","publication_year":2000,"publication_date":"2000-04-01","ids":{"openalex":"https://openalex.org/W1993281691","doi":"https://doi.org/10.1002/(sici)1520-684x(200004)31:4<98::aid-scj10>3.0.co;2-j","mag":"1993281691"},"language":"en","primary_location":{"id":"doi:10.1002/(sici)1520-684x(200004)31:4<98::aid-scj10>3.0.co;2-j","is_oa":false,"landing_page_url":"https://doi.org/10.1002/(sici)1520-684x(200004)31:4<98::aid-scj10>3.0.co;2-j","pdf_url":null,"source":{"id":"https://openalex.org/S58208175","display_name":"Systems and Computers in Japan","issn_l":"0882-1666","issn":["0882-1666","1520-684X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems and Computers in Japan","raw_type":"journal-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/A5113483611","display_name":"Yoshinaga Kato","orcid":null},"institutions":[{"id":"https://openalex.org/I24193003","display_name":"Ricoh (Japan)","ror":"https://ror.org/02h4myp42","country_code":"JP","type":"company","lineage":["https://openalex.org/I24193003"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshinaga Kato","raw_affiliation_strings":["Software Research Center, Ricoh Company, Ltd., Yokohama, Japan 222-8530"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Software Research Center, Ricoh Company, Ltd., Yokohama, Japan 222-8530","institution_ids":["https://openalex.org/I24193003"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049171444","display_name":"Tetsuya Muroi","orcid":null},"institutions":[{"id":"https://openalex.org/I24193003","display_name":"Ricoh (Japan)","ror":"https://ror.org/02h4myp42","country_code":"JP","type":"company","lineage":["https://openalex.org/I24193003"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuya Muroi","raw_affiliation_strings":["Software Research Center, Ricoh Company, Ltd., Yokohama, Japan 222-8530"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Software Research Center, Ricoh Company, Ltd., Yokohama, Japan 222-8530","institution_ids":["https://openalex.org/I24193003"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24193003"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10401373,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"31","issue":"4","first_page":"98","last_page":"108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.998199999332428,"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/T10320","display_name":"Neural Networks and Applications","score":0.998199999332428,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9850000143051147,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9685999751091003,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8148897886276245},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.7293063402175903},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6955543756484985},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic time warping","score":0.652438223361969},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6052438616752625},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5056328773498535},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.4856390058994293},{"id":"https://openalex.org/keywords/hidden-semi-markov-model","display_name":"Hidden semi-Markov model","score":0.4604419469833374},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.4585539698600769},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43724942207336426},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.3997068405151367},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.21310150623321533},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.18831363320350647}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8148897886276245},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.7293063402175903},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955543756484985},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.652438223361969},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6052438616752625},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5056328773498535},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.4856390058994293},{"id":"https://openalex.org/C64939953","wikidata":"https://www.wikidata.org/wiki/Q3859882","display_name":"Hidden semi-Markov model","level":5,"score":0.4604419469833374},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.4585539698600769},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43724942207336426},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.3997068405151367},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.21310150623321533},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.18831363320350647},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C189973286","wikidata":"https://www.wikidata.org/wiki/Q176695","display_name":"Markov property","level":4,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/(sici)1520-684x(200004)31:4<98::aid-scj10>3.0.co;2-j","is_oa":false,"landing_page_url":"https://doi.org/10.1002/(sici)1520-684x(200004)31:4<98::aid-scj10>3.0.co;2-j","pdf_url":null,"source":{"id":"https://openalex.org/S58208175","display_name":"Systems and Computers in Japan","issn_l":"0882-1666","issn":["0882-1666","1520-684X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems and Computers in Japan","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.8100000023841858,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W148494291","https://openalex.org/W1533051419","https://openalex.org/W2000885660","https://openalex.org/W2008894165","https://openalex.org/W2010764240","https://openalex.org/W2063541597","https://openalex.org/W2064218608","https://openalex.org/W2105080323","https://openalex.org/W2155126530","https://openalex.org/W6605936404","https://openalex.org/W6652500256","https://openalex.org/W6675945144"],"related_works":["https://openalex.org/W1510894296","https://openalex.org/W2379938888","https://openalex.org/W4246505579","https://openalex.org/W2134386692","https://openalex.org/W2103649304","https://openalex.org/W3044198794","https://openalex.org/W2116722627","https://openalex.org/W2176285001","https://openalex.org/W2537260108","https://openalex.org/W2799426416"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"a":[3,11,32,90,117,129,155],"new":[4],"duration-based":[5,52,91],"state":[6,53],"transition":[7,54],"model":[8,55,110,153],"that":[9,78,98,134,180,212],"incorporates":[10],"discriminative":[12,76],"weighting":[13,45],"parameter.":[14],"The":[15,171],"serious":[16],"problem":[17],"of":[18,50,108,140,151,162,174],"acoustical/temporal":[19],"variation":[20],"in":[21,71],"different":[22],"speakers'":[23],"utterances":[24],"has":[25],"long":[26],"made":[27],"it":[28],"difficult":[29],"to":[30,154,166,188,203],"design":[31],"robust":[33],"speech":[34,87],"recognition":[35,141,178,190,197],"model.":[36,170],"To":[37],"cope":[38],"with":[39],"this":[40,152],"problem,":[41],"we":[42],"integrate":[43],"state-dependent":[44,66,182],"parameters":[46,111],"into":[47],"the":[48,51,58,61,82,86,109,138,149,163,167,196,209,213],"structure":[49],"and":[56,74,160,184],"control":[57,186],"score":[59,84],"for":[60,85,193],"accompanying":[62],"temporal":[63],"segment.":[64],"These":[65],"weightings":[67,183],"absorb":[68],"local":[69],"variations":[70],"an":[72],"utterance":[73],"provide":[75],"ability":[77],"can":[79,135],"directly":[80,136],"influence":[81],"total":[83],"pattern.":[88],"Moreover,":[89],"matching":[92],"procedure":[93],"precludes":[94],"stiff":[95],"dynamic":[96],"warping":[97],"involves":[99],"excessive":[100],"time":[101],"stretching":[102],"or":[103],"compression.":[104],"We":[105,146],"train":[106],"all":[107],"including":[112],"proposed":[113],"parameters,":[114],"by":[115,128],"using":[116,208],"minimum":[118],"classification":[119,123],"error":[120,124],"criterion.":[121],"Minimum":[122],"training":[125,165,214],"is":[126],"implemented":[127],"generalized":[130],"probabilistic":[131],"descent":[132],"method":[133],"minimize":[137],"number":[139],"errors":[142],"between":[143],"competing":[144],"models.":[145],"also":[147],"discuss":[148],"relationship":[150],"conventional":[156],"hidden":[157,168],"Markov":[158,169],"model,":[159],"applicability":[161],"minimum-classification-error/generalized-probabilistic-descent":[164],"experimental":[172],"results":[173],"spotting-based":[175],"speaker-independent":[176],"word":[177],"show":[179],"both":[181],"duration":[185],"helped":[187],"improve":[189],"performance.":[191],"Furthermore,":[192],"low-performance":[194],"speakers,":[195],"rate":[198],"was":[199,215],"raised":[200],"from":[201],"65.5%":[202],"92.0%":[204],"after":[205],"speaker":[206],"adaptation":[207],"training,":[210],"proving":[211],"effective.":[216],"\u00a9":[217],"2000":[218,226],"Scripta":[219],"Technica,":[220],"Syst":[221],"Comp":[222],"Jpn,":[223],"31(4):":[224],"98\u2013108,":[225]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}