{"id":"https://openalex.org/W2078234404","doi":"https://doi.org/10.1109/tasl.2013.2244087","title":"Improving Statistical Machine Translation Using Bayesian Word Alignment and Gibbs Sampling","display_name":"Improving Statistical Machine Translation Using Bayesian Word Alignment and Gibbs Sampling","publication_year":2013,"publication_date":"2013-01-31","ids":{"openalex":"https://openalex.org/W2078234404","doi":"https://doi.org/10.1109/tasl.2013.2244087","mag":"2078234404"},"language":"en","primary_location":{"id":"doi:10.1109/tasl.2013.2244087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2013.2244087","pdf_url":null,"source":{"id":"https://openalex.org/S199497470","display_name":"IEEE Transactions on Audio Speech and Language Processing","issn_l":"1558-7916","issn":["1558-7916","1558-7924"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Audio, Speech, and Language Processing","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/A5061157470","display_name":"Co\u015fkun Mermer","orcid":"https://orcid.org/0000-0002-7740-6813"},"institutions":[{"id":"https://openalex.org/I4210141511","display_name":"TUBITAK BILGEM","ror":"https://ror.org/057kvja37","country_code":"TR","type":"government","lineage":["https://openalex.org/I4210141511"]},{"id":"https://openalex.org/I4405392","display_name":"Bo\u011fazi\u00e7i University","ror":"https://ror.org/03z9tma90","country_code":"TR","type":"education","lineage":["https://openalex.org/I4405392"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Co\u015fkun Mermer","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Bo\u011fazi\u00e7i University, Istanbul, Turkey","T\u00dcB\u0130TAK B\u0130LGEM, Kocaeli, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Bo\u011fazi\u00e7i University, Istanbul, Turkey","institution_ids":["https://openalex.org/I4405392"]},{"raw_affiliation_string":"T\u00dcB\u0130TAK B\u0130LGEM, Kocaeli, Turkey","institution_ids":["https://openalex.org/I4210141511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055086464","display_name":"Murat Sara\u00e7lar","orcid":"https://orcid.org/0000-0002-7435-8510"},"institutions":[{"id":"https://openalex.org/I4405392","display_name":"Bo\u011fazi\u00e7i University","ror":"https://ror.org/03z9tma90","country_code":"TR","type":"education","lineage":["https://openalex.org/I4405392"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Murat Saraclar","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Bo\u011fazi\u00e7i University, Istanbul, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Bo\u011fazi\u00e7i University, Istanbul, Turkey","institution_ids":["https://openalex.org/I4405392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072875068","display_name":"Ruhi Sarikaya","orcid":"https://orcid.org/0000-0003-2676-2831"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruhi Sarikaya","raw_affiliation_strings":["Microsoft Corporation, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5061157470"],"corresponding_institution_ids":["https://openalex.org/I4210141511","https://openalex.org/I4405392"],"apc_list":null,"apc_paid":null,"fwci":5.2901,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.95426413,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"21","issue":"5","first_page":"1090","last_page":"1101"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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/T10181","display_name":"Natural Language Processing Techniques","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/T10028","display_name":"Topic Modeling","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/T13629","display_name":"Text Readability and Simplification","score":0.9854999780654907,"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/gibbs-sampling","display_name":"Gibbs sampling","score":0.7675263285636902},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7500474452972412},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6987088322639465},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6040709614753723},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5899168252944946},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5481406450271606},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5066900849342346},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.5035173296928406},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.48774605989456177},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.44032353162765503},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1815030872821808}],"concepts":[{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.7675263285636902},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7500474452972412},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6987088322639465},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6040709614753723},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5899168252944946},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5481406450271606},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5066900849342346},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.5035173296928406},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.48774605989456177},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.44032353162765503},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1815030872821808},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tasl.2013.2244087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tasl.2013.2244087","pdf_url":null,"source":{"id":"https://openalex.org/S199497470","display_name":"IEEE Transactions on Audio Speech and Language Processing","issn_l":"1558-7916","issn":["1558-7916","1558-7924"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Audio, Speech, and Language Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.800000011920929,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":78,"referenced_works":["https://openalex.org/W11511616","https://openalex.org/W45604574","https://openalex.org/W653042059","https://openalex.org/W1631260214","https://openalex.org/W1767083593","https://openalex.org/W1895815892","https://openalex.org/W1916559533","https://openalex.org/W1979102019","https://openalex.org/W2004316800","https://openalex.org/W2006969979","https://openalex.org/W2020999234","https://openalex.org/W2030750105","https://openalex.org/W2038698865","https://openalex.org/W2045238294","https://openalex.org/W2049633694","https://openalex.org/W2080373976","https://openalex.org/W2086202918","https://openalex.org/W2087735403","https://openalex.org/W2095907708","https://openalex.org/W2099873701","https://openalex.org/W2100269333","https://openalex.org/W2101105183","https://openalex.org/W2105577415","https://openalex.org/W2115526192","https://openalex.org/W2116137244","https://openalex.org/W2116594867","https://openalex.org/W2122228338","https://openalex.org/W2124807415","https://openalex.org/W2126270798","https://openalex.org/W2134409515","https://openalex.org/W2136657878","https://openalex.org/W2137122906","https://openalex.org/W2140991203","https://openalex.org/W2144600658","https://openalex.org/W2149327368","https://openalex.org/W2150066400","https://openalex.org/W2151197196","https://openalex.org/W2153653739","https://openalex.org/W2156985047","https://openalex.org/W2158195707","https://openalex.org/W2160721348","https://openalex.org/W2161742089","https://openalex.org/W2162465526","https://openalex.org/W2164151151","https://openalex.org/W2165666205","https://openalex.org/W2166044723","https://openalex.org/W2169724380","https://openalex.org/W2169755259","https://openalex.org/W2172138510","https://openalex.org/W2251167004","https://openalex.org/W2437005631","https://openalex.org/W2527859316","https://openalex.org/W2760567570","https://openalex.org/W2917362697","https://openalex.org/W2917604489","https://openalex.org/W6600454326","https://openalex.org/W6601859171","https://openalex.org/W6637920729","https://openalex.org/W6639736754","https://openalex.org/W6652311901","https://openalex.org/W6674903454","https://openalex.org/W6675002571","https://openalex.org/W6677121468","https://openalex.org/W6678164431","https://openalex.org/W6680129566","https://openalex.org/W6680141653","https://openalex.org/W6681644459","https://openalex.org/W6681703963","https://openalex.org/W6682084000","https://openalex.org/W6684044740","https://openalex.org/W6684410512","https://openalex.org/W6684652477","https://openalex.org/W6686685866","https://openalex.org/W6691304694","https://openalex.org/W6697079997","https://openalex.org/W6728525635","https://openalex.org/W6744757472","https://openalex.org/W6898505805"],"related_works":["https://openalex.org/W840335986","https://openalex.org/W1517763961","https://openalex.org/W1501929113","https://openalex.org/W2133543800","https://openalex.org/W3122927555","https://openalex.org/W1990075812","https://openalex.org/W2494929626","https://openalex.org/W4378501308","https://openalex.org/W3161345512","https://openalex.org/W4311691341"],"abstract_inverted_index":{"We":[0,49,93],"present":[1],"a":[2,41],"Bayesian":[3,96],"approach":[4],"to":[5,53,88,143],"word":[6,19,56,61,121,128],"alignment":[7,57],"inference":[8,71,97],"in":[9,72,103,123,130],"IBM":[10],"Models":[11],"1":[12],"and":[13,43,67,83,101,125,135,141],"2.":[14],"In":[15,32],"the":[16,28,33,55,104,113,118],"original":[17],"approach,":[18,35],"translation":[20,77],"probabilities":[21],"(i.e.,":[22],"model":[23],"parameters)":[24],"are":[25,37,44,63],"estimated":[26],"using":[27],"expectation-maximization":[29],"(EM)":[30],"algorithm.":[31],"proposed":[34,114],"they":[36],"random":[38],"variables":[39],"with":[40],"prior":[42],"integrated":[45],"out":[46],"during":[47],"inference.":[48],"use":[50],"Gibbs":[51],"sampling":[52],"infer":[54],"posteriors.":[58],"The":[59],"inferred":[60],"alignments":[62],"compared":[64],"against":[65],"EM":[66,100,124],"variational":[68],"Bayes":[69],"(VB)":[70],"terms":[73],"of":[74,85,106],"their":[75],"end-to-end":[76],"performance":[78],"on":[79],"several":[80],"language":[81],"pairs":[82],"types":[84],"corpora":[86],"up":[87],"15":[89],"million":[90],"sentence":[91],"pairs.":[92],"show":[94],"that":[95,112],"outperforms":[98],"both":[99],"VB":[102],"majority":[105],"test":[107],"cases.":[108],"Further":[109],"analysis":[110],"reveals":[111],"method":[115],"effectively":[116],"addresses":[117],"high-fertility":[119],"rare":[120,127],"problem":[122,129],"unaligned":[126],"VB,":[131],"achieves":[132],"higher":[133],"agreement":[134],"vocabulary":[136],"coverage":[137],"rates":[138],"than":[139],"both,":[140],"leads":[142],"smaller":[144],"phrase":[145],"tables.":[146]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}