{"id":"https://openalex.org/W1773599773","doi":"https://doi.org/10.1109/icassp.2015.7179006","title":"Unnormalized exponential and neural network language models","display_name":"Unnormalized exponential and neural network language models","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1773599773","doi":"https://doi.org/10.1109/icassp.2015.7179006","mag":"1773599773"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2015.7179006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2015.7179006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5088302697","display_name":"Abhinav Sethy","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"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 T.J. Watson Research Center, Yorktown Heights, NY, USA","IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM T.J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111644958","display_name":"Stanley Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"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 Chen","raw_affiliation_strings":["IBM T.J. Watson Research Center, Yorktown Heights, NY, USA","IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM T.J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032284977","display_name":"Ebru Ar\u0131soy","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"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":"Ebru Arisoy","raw_affiliation_strings":["IBM T.J. Watson Research Center, Yorktown Heights, NY, USA","IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM T.J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071715737","display_name":"Bhuvana Ramabhadran","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"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 T.J. Watson Research Center, Yorktown Heights, NY, USA","IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM T.J. Watson Research Center, Yorktown Heights, NY, USA","institution_ids":["https://openalex.org/I4210114115"]},{"raw_affiliation_string":"IBM T. J. Watson Research Center, Yorktown Heights , NY, USA#TAB#","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"5416","last_page":"5420"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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"}},"topics":[{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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/T10028","display_name":"Topic Modeling","score":0.9995999932289124,"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":0.9987000226974487,"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/softmax-function","display_name":"Softmax function","score":0.9426150321960449},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8131307363510132},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.7940574884414673},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.6208304166793823},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5772494077682495},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5536096692085266},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5529855489730835},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5464826822280884},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5263184905052185},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.518631637096405},{"id":"https://openalex.org/keywords/exponential-function","display_name":"Exponential function","score":0.5164482593536377},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5024476051330566},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.49596843123435974},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4813002645969391},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3306090235710144},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2707057297229767},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1283535659313202},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12002363801002502},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08266833424568176}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9426150321960449},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8131307363510132},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.7940574884414673},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.6208304166793823},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5772494077682495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5536096692085266},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5529855489730835},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5464826822280884},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5263184905052185},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.518631637096405},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.5164482593536377},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5024476051330566},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.49596843123435974},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4813002645969391},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3306090235710144},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2707057297229767},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1283535659313202},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12002363801002502},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08266833424568176},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2015.7179006","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2015.7179006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8799999952316284}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W36200081","https://openalex.org/W932413789","https://openalex.org/W1964742985","https://openalex.org/W1970689298","https://openalex.org/W1979625042","https://openalex.org/W1986468312","https://openalex.org/W2020382207","https://openalex.org/W2020683423","https://openalex.org/W2037942319","https://openalex.org/W2050971845","https://openalex.org/W2091981305","https://openalex.org/W2098318492","https://openalex.org/W2110415041","https://openalex.org/W2112739286","https://openalex.org/W2120861206","https://openalex.org/W2130917146","https://openalex.org/W2138204974","https://openalex.org/W2146183716","https://openalex.org/W2157112198","https://openalex.org/W2185726469","https://openalex.org/W2396033037","https://openalex.org/W2962719052","https://openalex.org/W2998704965","https://openalex.org/W4285719527","https://openalex.org/W6601500749","https://openalex.org/W6624558595","https://openalex.org/W6646791905","https://openalex.org/W6678040779","https://openalex.org/W6679744255","https://openalex.org/W6680106237","https://openalex.org/W6680532216","https://openalex.org/W6683140599","https://openalex.org/W6686651311"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W4226420367","https://openalex.org/W2962876041","https://openalex.org/W3090555870","https://openalex.org/W3022820045","https://openalex.org/W1997182898","https://openalex.org/W2268150819","https://openalex.org/W2944691285"],"abstract_inverted_index":{"Model":[0,75],"M,":[1],"an":[2],"exponential":[3],"class-based":[4],"language":[5,10,17],"model,":[6],"and":[7,77],"neural":[8],"network":[9],"models":[11,18,116],"(NNLM's)":[12],"have":[13],"outperformed":[14],"word":[15,38,56],"n-gram":[16,112],"over":[19,53,117],"a":[20,54,107],"wide":[21],"range":[22],"of":[23,32,45,74,109],"tasks.":[24],"However,":[25],"these":[26],"gains":[27],"come":[28],"at":[29],"the":[30,43,50,80,130],"cost":[31],"vastly":[33],"increased":[34],"computation":[35,47],"when":[36],"calculating":[37],"probabilities.":[39],"For":[40],"both":[41],"models,":[42],"bulk":[44],"this":[46,68,101],"involves":[48],"evaluating":[49],"softmax":[51,81],"function":[52,82],"large":[55],"or":[57],"class":[58],"vocabulary":[59],"to":[60,65,92,95,98,106],"ensure":[61],"that":[62],"probabilities":[63],"sum":[64,96],"1.":[66,99],"In":[67,100],"paper,":[69,102],"we":[70,103],"study":[71],"unnormalized":[72,115],"variants":[73],"M":[76],"NNLM's,":[78],"whereby":[79],"is":[83],"simply":[84],"omitted.":[85],"Accordingly,":[86],"model":[87],"training":[88],"must":[89],"be":[90],"modified":[91],"encourage":[93],"scores":[94],"close":[97],"demonstrate":[104],"up":[105],"factor":[108],"35":[110],"faster":[111],"lookups":[113],"with":[114],"their":[118],"normalized":[119],"counterparts,":[120],"while":[121],"still":[122],"yielding":[123],"state-of-the-art":[124],"performance":[125],"in":[126],"WER":[127],"(10.2":[128],"on":[129],"English":[131],"broadcast":[132],"news":[133],"rt04":[134],"set).":[135]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
