{"id":"https://openalex.org/W2172045870","doi":"https://doi.org/10.1109/asru.2009.5373338","title":"Constrained discriminative training of N-gram language models","display_name":"Constrained discriminative training of N-gram language models","publication_year":2009,"publication_date":"2009-12-01","ids":{"openalex":"https://openalex.org/W2172045870","doi":"https://doi.org/10.1109/asru.2009.5373338","mag":"2172045870"},"language":"en","primary_location":{"id":"doi:10.1109/asru.2009.5373338","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru.2009.5373338","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Workshop on Automatic Speech Recognition & Understanding","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/A5110230355","display_name":"Ariya Rastrow","orcid":null},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ariya Rastrow","raw_affiliation_strings":["Center for Language and Speech Processing, Johns Hopkins University, MD, USA"],"affiliations":[{"raw_affiliation_string":"Center for Language and Speech Processing, Johns Hopkins University, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088302697","display_name":"Abhinav Sethy","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abhinav Sethy","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071715737","display_name":"Bhuvana Ramabhadran","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bhuvana Ramabhadran","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5110230355"],"corresponding_institution_ids":["https://openalex.org/I145311948"],"apc_list":null,"apc_paid":null,"fwci":2.1809,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.89831549,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"311","last_page":"316"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9991999864578247,"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":0.9986000061035156,"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/discriminative-model","display_name":"Discriminative model","score":0.9504023194313049},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7679712772369385},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.7152532935142517},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.6978824138641357},{"id":"https://openalex.org/keywords/n-gram","display_name":"n-gram","score":0.6446831226348877},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.6017948985099792},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5492586493492126},{"id":"https://openalex.org/keywords/gram","display_name":"Gram","score":0.43390369415283203},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34239113330841064},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33724790811538696}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9504023194313049},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7679712772369385},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7152532935142517},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.6978824138641357},{"id":"https://openalex.org/C117884012","wikidata":"https://www.wikidata.org/wiki/Q94489","display_name":"n-gram","level":3,"score":0.6446831226348877},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.6017948985099792},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5492586493492126},{"id":"https://openalex.org/C161369605","wikidata":"https://www.wikidata.org/wiki/Q41803","display_name":"Gram","level":3,"score":0.43390369415283203},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34239113330841064},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33724790811538696},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C523546767","wikidata":"https://www.wikidata.org/wiki/Q10876","display_name":"Bacteria","level":2,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asru.2009.5373338","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru.2009.5373338","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Workshop on Automatic Speech Recognition & Understanding","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1481751294","https://openalex.org/W1797288984","https://openalex.org/W2005076803","https://openalex.org/W2091466535","https://openalex.org/W2097927681","https://openalex.org/W2098318492","https://openalex.org/W2110467295","https://openalex.org/W2138309071","https://openalex.org/W2140281218","https://openalex.org/W2158025800","https://openalex.org/W2158148237","https://openalex.org/W2169384404","https://openalex.org/W2950186769","https://openalex.org/W4230318854","https://openalex.org/W6628832040","https://openalex.org/W6638218882","https://openalex.org/W6651845459","https://openalex.org/W6684930139"],"related_works":["https://openalex.org/W2906970013","https://openalex.org/W3126081632","https://openalex.org/W1617617605","https://openalex.org/W2088254117","https://openalex.org/W4254593385","https://openalex.org/W2790582133","https://openalex.org/W2113687551","https://openalex.org/W2250909759","https://openalex.org/W2532616038","https://openalex.org/W2112752961"],"abstract_inverted_index":{"In":[0,70],"this":[1,71],"paper,":[2,72],"we":[3,73],"present":[4,74,115],"a":[5,52,99,103,116,124],"novel":[6],"version":[7],"of":[8,41,51,82,89,93,121,150],"discriminative":[9,39,57,80,119],"training":[10,40,58,81],"for":[11,59,118],"N-gram":[12,60,95,110],"language":[13,18,61],"models.":[14],"Language":[15],"models":[16,43,62],"impose":[17],"specific":[19],"constraints":[20],"on":[21,108,138],"the":[22,37,49,67,79,86,94,109,139,143],"acoustic":[23,32,42],"hypothesis":[24],"and":[25,102,127,142,156],"are":[26,136],"crucial":[27],"in":[28,36,48],"discriminating":[29],"between":[30],"competing":[31],"hypotheses.":[33],"As":[34],"reported":[35,137],"literature,":[38],"has":[44,64],"yielded":[45,66],"significant":[46],"improvements":[47],"performance":[50],"speech":[53],"recognition":[54],"system,":[55],"however,":[56],"(LMs)":[63],"not":[65],"same":[68],"impact.":[69],"three":[75],"techniques":[76],"to":[77,97,123,130],"improve":[78],"LMs,":[83],"namely":[84],"updating":[85],"back-off":[87],"probability":[88,100,111],"unseen":[90],"events,":[91],"normalization":[92],"updates":[96],"ensure":[98],"distribution":[101],"relative-entropy":[104],"based":[105],"global":[106],"constraint":[107],"updates.":[112],"We":[113],"also":[114],"framework":[117],"adaptation":[120],"LMs":[122,167],"new":[125],"domain":[126],"compare":[128],"it":[129],"existing":[131],"linear":[132],"interpolation":[133],"methods.":[134],"Results":[135],"Broadcast":[140,154],"News":[141],"MIT":[144,160],"lecture":[145],"corpora.":[146],"A":[147],"modest":[148],"improvement":[149],"0.2%":[151],"absolute":[152,158],"(on":[153,159],"News)":[155],"0.3%":[157],"lectures)":[161],"was":[162],"observed":[163],"with":[164],"discriminatively":[165],"trained":[166],"over":[168],"state-of-the-art":[169],"systems.":[170]},"counts_by_year":[{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}