{"id":"https://openalex.org/W2162553934","doi":"https://doi.org/10.1109/icassp.2011.5947608","title":"Multi-class Model M","display_name":"Multi-class Model M","publication_year":2011,"publication_date":"2011-05-01","ids":{"openalex":"https://openalex.org/W2162553934","doi":"https://doi.org/10.1109/icassp.2011.5947608","mag":"2162553934"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2011.5947608","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2011.5947608","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5080675607","display_name":"Ahmad Emami","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":"Ahmad Emami","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA"],"raw_orcid":null,"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/A5090361189","display_name":"Stanley F. Chen","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":"Stanley F. Chen","raw_affiliation_strings":["IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA"],"raw_orcid":null,"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":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3189,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.85203502,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"18","issue":null,"first_page":"5516","last_page":"5519"},"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9977999925613403,"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/computer-science","display_name":"Computer science","score":0.7859781980514526},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.781023383140564},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.7729234099388123},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6784033179283142},{"id":"https://openalex.org/keywords/machine-translation","display_name":"Machine translation","score":0.6498794555664062},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.643131673336029},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.6416330933570862},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5755558609962463},{"id":"https://openalex.org/keywords/n-gram","display_name":"n-gram","score":0.5648623108863831},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4391135275363922},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14591899514198303}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7859781980514526},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.781023383140564},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.7729234099388123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6784033179283142},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.6498794555664062},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.643131673336029},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.6416330933570862},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5755558609962463},{"id":"https://openalex.org/C117884012","wikidata":"https://www.wikidata.org/wiki/Q94489","display_name":"n-gram","level":3,"score":0.5648623108863831},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4391135275363922},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14591899514198303},{"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/icassp.2011.5947608","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2011.5947608","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7699999809265137}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332178","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W47415966","https://openalex.org/W94354135","https://openalex.org/W122584218","https://openalex.org/W1974515274","https://openalex.org/W2050971845","https://openalex.org/W2080018251","https://openalex.org/W2111305191","https://openalex.org/W2117238933","https://openalex.org/W2121227244","https://openalex.org/W2148321140","https://openalex.org/W2437005631","https://openalex.org/W6678277124"],"related_works":["https://openalex.org/W2250909759","https://openalex.org/W2787311093","https://openalex.org/W2532616038","https://openalex.org/W2057384730","https://openalex.org/W4307474317","https://openalex.org/W2147879411","https://openalex.org/W2624072012","https://openalex.org/W2008468404","https://openalex.org/W2132221452","https://openalex.org/W2081295016"],"abstract_inverted_index":{"Model":[0,57,76],"M,":[1],"a":[2,53],"novel":[3],"class-based":[4,54],"exponential":[5,42],"language":[6,43,55],"model,":[7,56],"has":[8],"been":[9],"shown":[10],"to":[11,46,78,83],"significantly":[12],"outperform":[13],"word":[14,62,88],"n-gram":[15],"models":[16],"in":[17,40,105,121],"state-of-the-art":[18],"machine":[19,122],"translation":[20,123],"and":[21,112,116],"speech":[22],"recognition":[23],"systems.":[24],"The":[25],"model":[26,44],"was":[27],"motivated":[28,92],"by":[29,93,127],"the":[30,34,37,94],"observation":[31],"that":[32,64,96],"shrinking":[33],"sum":[35],"of":[36,61],"parameter":[38],"magnitudes":[39],"an":[41,106],"leads":[45],"better":[47],"performance":[48],"on":[49,102,109],"unseen":[50],"data.":[51,70],"Being":[52],"M":[58,77],"makes":[59],"use":[60],"classes":[63],"are":[65],"found":[66],"automatically":[67],"from":[68],"training":[69],"In":[71],"this":[72],"paper,":[73],"we":[74],"extend":[75],"allow":[79],"for":[80],"different":[81,87,99],"clusterings":[82],"be":[84],"used":[85],"at":[86],"positions.":[89],"This":[90],"is":[91],"fact":[95],"words":[97],"play":[98],"roles":[100],"depending":[101],"their":[103],"position":[104],"n-gram.":[107],"Experiments":[108],"standard":[110],"NIST":[111],"GALE":[113],"Arabic-to-English":[114],"development":[115],"test":[117],"sets":[118],"show":[119],"improvements":[120],"quality":[124],"as":[125],"measured":[126],"automatic":[128],"evaluation":[129],"metrics.":[130]},"counts_by_year":[{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
