{"id":"https://openalex.org/W2074818733","doi":"https://doi.org/10.1109/slt.2012.6424224","title":"Use of kernel deep convex networks and end-to-end learning for spoken language understanding","display_name":"Use of kernel deep convex networks and end-to-end learning for spoken language understanding","publication_year":2012,"publication_date":"2012-12-01","ids":{"openalex":"https://openalex.org/W2074818733","doi":"https://doi.org/10.1109/slt.2012.6424224","mag":"2074818733"},"language":"en","primary_location":{"id":"doi:10.1109/slt.2012.6424224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/slt.2012.6424224","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Spoken Language Technology Workshop (SLT)","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/A5100671324","display_name":"Li Deng","orcid":"https://orcid.org/0000-0002-1014-0790"},"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":true,"raw_author_name":"Li Deng","raw_affiliation_strings":["Microsoft Research, USA","Microsoft research#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft research#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087941479","display_name":"G\u00f6khan T\u00fcr","orcid":null},"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":"Gokhan Tur","raw_affiliation_strings":["Microsoft Research, USA","Microsoft research#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft research#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101727205","display_name":"Xiaodong He","orcid":"https://orcid.org/0000-0002-9463-9168"},"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":"Xiaodong He","raw_affiliation_strings":["Microsoft Research, USA","Microsoft research#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft research#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068709817","display_name":"Dilek Hakkani\u2010T\u00fcr","orcid":null},"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":"Dilek Hakkani-Tur","raw_affiliation_strings":["Microsoft Research, USA","Microsoft research#TAB#"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, USA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft research#TAB#","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100671324"],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":9.442,"has_fulltext":false,"cited_by_count":109,"citation_normalized_percentile":{"value":0.98426667,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"210","last_page":"215"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9991000294685364,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991000294685364,"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":0.9366344809532166},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7775272130966187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6299306750297546},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5757620334625244},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5556113719940186},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5016403198242188},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4573895037174225},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4320743978023529},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.41013529896736145},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3230500817298889}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9366344809532166},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7775272130966187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6299306750297546},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5757620334625244},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5556113719940186},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5016403198242188},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4573895037174225},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4320743978023529},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.41013529896736145},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3230500817298889}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/slt.2012.6424224","is_oa":false,"landing_page_url":"https://doi.org/10.1109/slt.2012.6424224","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Spoken Language Technology Workshop (SLT)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.306.6029","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.306.6029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/pubs/172597/SLT12-1.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W648947103","https://openalex.org/W1601795611","https://openalex.org/W1649407914","https://openalex.org/W1663973292","https://openalex.org/W1755117326","https://openalex.org/W1839113334","https://openalex.org/W1891101548","https://openalex.org/W1993882792","https://openalex.org/W2024539680","https://openalex.org/W2026131661","https://openalex.org/W2035221948","https://openalex.org/W2096557251","https://openalex.org/W2096635587","https://openalex.org/W2097550833","https://openalex.org/W2105565783","https://openalex.org/W2106347453","https://openalex.org/W2132403634","https://openalex.org/W2139269942","https://openalex.org/W2139622435","https://openalex.org/W2140881187","https://openalex.org/W2141778357","https://openalex.org/W2146574666","https://openalex.org/W2147768505","https://openalex.org/W2149600041","https://openalex.org/W2150859660","https://openalex.org/W2158899491","https://openalex.org/W2160815625","https://openalex.org/W2166293310","https://openalex.org/W2168013545","https://openalex.org/W2168029744","https://openalex.org/W2170780515","https://openalex.org/W2184045248","https://openalex.org/W2952230511","https://openalex.org/W3101749733","https://openalex.org/W6637962894","https://openalex.org/W6656819595","https://openalex.org/W6674743151","https://openalex.org/W6675545515","https://openalex.org/W6680508596","https://openalex.org/W6681419218","https://openalex.org/W6683738474","https://openalex.org/W6684017090"],"related_works":["https://openalex.org/W3095152779","https://openalex.org/W3119773509","https://openalex.org/W3128220219","https://openalex.org/W3006353185","https://openalex.org/W2116862786","https://openalex.org/W2947839263","https://openalex.org/W3120400911","https://openalex.org/W2988321605","https://openalex.org/W2830281438","https://openalex.org/W4382934300"],"abstract_inverted_index":{"We":[0,48],"present":[1],"our":[2],"recent":[3],"and":[4,65,95,154],"ongoing":[5],"work":[6],"on":[7,68],"applying":[8],"deep":[9,21],"learning":[10,143,159],"techniques":[11],"to":[12,27,128],"spoken":[13],"language":[14],"understanding":[15],"(SLU)":[16],"problems.":[17],"The":[18,124],"previously":[19],"developed":[20],"convex":[22],"network":[23],"(DCN)":[24],"is":[25,136],"extended":[26],"its":[28],"kernel":[29,46],"version":[30],"(K-DCN)":[31],"where":[32,157],"the":[33,45,58,62,66,118,133,147,158,167,170],"number":[34],"of":[35,73,81,122,126],"hidden":[36],"units":[37],"in":[38],"each":[39],"DCN":[40,67,94,153],"layer":[41],"approaches":[42],"infinity":[43],"using":[44],"trick.":[47],"report":[49],"experimental":[50],"results":[51],"demonstrating":[52],"dramatic":[53],"error":[54],"reduction":[55],"achieved":[56],"by":[57],"K-DCN":[59,96,127,155],"over":[60],"both":[61],"Boosting-based":[63],"baseline":[64],"a":[69,77,100],"domain":[70,101],"classification":[71],"task":[72,121],"SLU,":[74,106],"especially":[75],"when":[76],"highly":[78],"correlated":[79],"set":[80],"features":[82],"extracted":[83],"from":[84],"search":[85],"query":[86],"click":[87],"logs":[88],"are":[89],"used.":[90],"Not":[91],"only":[92],"can":[93,108,161],"be":[97,110],"used":[98,111],"as":[99,112],"or":[102],"intent":[103],"classifier":[104],"for":[105,117,145,169],"they":[107],"also":[109],"local,":[113],"discriminative":[114],"feature":[115],"extractors":[116],"slot":[119,129],"filling":[120,130],"SLU.":[123],"interface":[125],"systems":[131],"via":[132],"softmax":[134,148],"function":[135],"presented.":[137],"Finally,":[138],"we":[139],"outline":[140],"an":[141],"end-to-end":[142],"strategy":[144],"training":[146],"parameters":[149],"(and":[150],"potentially":[151],"all":[152],"parameters)":[156],"objective":[160],"take":[162],"any":[163],"performance":[164],"measure":[165],"(e.g.":[166],"F-measure)":[168],"full":[171],"SLU":[172],"system.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":11},{"year":2015,"cited_by_count":9},{"year":2014,"cited_by_count":13},{"year":2013,"cited_by_count":11},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}