{"id":"https://openalex.org/W123715776","doi":null,"title":"A Re-estimation Method for Stochastic Language Modeling from Ambiguous Observations","display_name":"A Re-estimation Method for Stochastic Language Modeling from Ambiguous Observations","publication_year":1996,"publication_date":"1996-01-01","ids":{"openalex":"https://openalex.org/W123715776","mag":"123715776"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.15.30","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.30","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://acl.ldc.upenn.edu/W/W96/W96-0113.pdf","raw_type":"text"},"volume":null,"type":"article","indexed_in":[],"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/A5112451327","display_name":"Mikio Yamamoto","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mikio Yamamoto","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5112451327"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3916,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.88768037,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9922000169754028,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9922000169754028,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.006099999882280827,"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/T12031","display_name":"Speech and dialogue systems","score":0.0010000000474974513,"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/statistical-language-models","display_name":"statistical language models","score":0.7120000123977661},{"id":"https://openalex.org/keywords/re-estimation","display_name":"re-estimation","score":0.8740000128746033},{"id":"https://openalex.org/keywords/n-gram-language-models","display_name":"n-gram language models","score":0.8730000257492065},{"id":"https://openalex.org/keywords/hidden-markov-models","display_name":"hidden Markov models","score":0.9459999799728394},{"id":"https://openalex.org/keywords/part-of-speech-tagging","display_name":"part-of-speech tagging","score":0.8989999890327454},{"id":"https://openalex.org/keywords/japanese-text","display_name":"Japanese text","score":0.7250000238418579},{"id":"https://openalex.org/keywords/noisy-training-data","display_name":"noisy training data","score":0.8140000104904175}],"concepts":[{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5885545611381531},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5805044174194336},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33960068225860596},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10981610417366028},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.15.30","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.30","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://acl.ldc.upenn.edu/W/W96/W96-0113.pdf","raw_type":"text"},{"id":"mag:123715776","doi":null,"is_oa":false,"landing_page_url":"https://www.aclweb.org/anthology/W96-0113.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419219","display_name":"International Conference on Computational Linguistics","issn_l":"1525-2477","issn":["1525-2477"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Computational Linguistics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W186138571","https://openalex.org/W1560013842","https://openalex.org/W1968953480","https://openalex.org/W1997644175","https://openalex.org/W2046224275","https://openalex.org/W2100796029","https://openalex.org/W2112861996","https://openalex.org/W2441154163"],"related_works":["https://openalex.org/W2556695754","https://openalex.org/W2316323787","https://openalex.org/W7098422188","https://openalex.org/W7095766991","https://openalex.org/W2112861996","https://openalex.org/W1934578773","https://openalex.org/W1974043298","https://openalex.org/W7097093851","https://openalex.org/W1998726122","https://openalex.org/W7098460577"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"a":[3,30,40,133,138],"reestimation":[4],"method":[5,61],"for":[6,29,82],"stochastic":[7,140],"language":[8,52,76,141],"models":[9,92],"such":[10],"as":[11,56,105,107],"the":[12,16,45,66,71,87,90,98,103,108,118],"N-gram":[13,46,67,109],"model":[14,27,47,110,125,142],"and":[15,117],"Hidden":[17],"Markov":[18],"Model(HMM)":[19],"from":[20,32,48,73,111,143],"ambiguous":[21],"observations.":[22],"It":[23],"is":[24,132],"applied":[25],"to":[26,39,85,136],"estination":[28],"tagger":[31],"an":[33,49,112],"untagged":[34,50,144],"corpus.":[35],"We":[36],"make":[37],"extensions":[38],"previous":[41],"algorithm":[42,100],"that":[43],"reestimates":[44],"segmented":[51],"(e.g.,":[53,77],"English)":[54],"text":[55],"training":[57,83],"data.":[58],"The":[59,127],"new":[60],"can":[62],"estimate":[63,102],"not":[64],"only":[65],"model,":[68],"but":[69],"also":[70,94],"HMM":[72,104],"untagged,":[74,113],"unsegmented":[75,114],"Japanese)":[78],"text.":[79],"Credit":[80],"factors":[81,131],"data":[84],"improve":[86],"reliability":[88],"of":[89,129],"estimated":[91],"are":[93,147],"introduced.":[95],"In":[96],"experiments,":[97],"extended":[99],"could":[101],"well":[106],"Japanese":[115],"corpus":[116],"credit":[119,130],"factor":[120],"was":[121],"effective":[122],"in":[123],"improving":[124],"accuracy.":[126],"use":[128],"useful":[134],"approach":[135],"estimating":[137],"reliable":[139],"corpora":[145],"which":[146],"noisy":[148],"by":[149],"nature.":[150]},"counts_by_year":[],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2016-06-24T00:00:00"}
