{"id":"https://openalex.org/W3200311007","doi":"https://doi.org/10.1109/asru51503.2021.9688109","title":"Remember the Context! ASR Slot Error Correction Through Memorization","display_name":"Remember the Context! ASR Slot Error Correction Through Memorization","publication_year":2021,"publication_date":"2021-12-13","ids":{"openalex":"https://openalex.org/W3200311007","doi":"https://doi.org/10.1109/asru51503.2021.9688109","mag":"3200311007"},"language":"en","primary_location":{"id":"doi:10.1109/asru51503.2021.9688109","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru51503.2021.9688109","pdf_url":null,"source":{"id":"https://openalex.org/S4363606113","display_name":"2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2109.05092","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020261049","display_name":"Dhanush Bekal","orcid":null},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dhanush Bekal","raw_affiliation_strings":["Amazon AWS AI,USA"],"affiliations":[{"raw_affiliation_string":"Amazon AWS AI,USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030041600","display_name":"Ashish Shenoy","orcid":"https://orcid.org/0000-0003-1401-262X"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ashish Shenoy","raw_affiliation_strings":["Amazon AWS AI,USA"],"affiliations":[{"raw_affiliation_string":"Amazon AWS AI,USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014130267","display_name":"Monica Sunkara","orcid":null},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Monica Sunkara","raw_affiliation_strings":["Amazon AWS AI,USA"],"affiliations":[{"raw_affiliation_string":"Amazon AWS AI,USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050552820","display_name":"Sravan Bodapati","orcid":null},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sravan Bodapati","raw_affiliation_strings":["Amazon AWS AI,USA"],"affiliations":[{"raw_affiliation_string":"Amazon AWS AI,USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050325468","display_name":"Katrin Kirchhoff","orcid":"https://orcid.org/0000-0002-6645-6030"},"institutions":[{"id":"https://openalex.org/I4210089985","display_name":"Amazon (Germany)","ror":"https://ror.org/00b9ktm87","country_code":"DE","type":"company","lineage":["https://openalex.org/I1311688040","https://openalex.org/I4210089985"]},{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"Katrin Kirchhoff","raw_affiliation_strings":["Amazon AWS AI,USA","Amazon"],"affiliations":[{"raw_affiliation_string":"Amazon AWS AI,USA","institution_ids":["https://openalex.org/I1311688040"]},{"raw_affiliation_string":"Amazon","institution_ids":["https://openalex.org/I4210089985"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5020261049"],"corresponding_institution_ids":["https://openalex.org/I1311688040"],"apc_list":null,"apc_paid":null,"fwci":0.127,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.34817552,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/T12031","display_name":"Speech and dialogue systems","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9997000098228455,"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":0.8347021341323853},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.7805272340774536},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6799356341362},{"id":"https://openalex.org/keywords/memorization","display_name":"Memorization","score":0.6555300951004028},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.6203139424324036},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5995208621025085},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5969004034996033},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.5730674266815186},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5327489376068115},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5299951434135437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5266321301460266},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5146147012710571},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5084725618362427},{"id":"https://openalex.org/keywords/named-entity-recognition","display_name":"Named-entity recognition","score":0.5080814361572266},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.47560223937034607},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4685916304588318},{"id":"https://openalex.org/keywords/error-detection-and-correction","display_name":"Error detection and correction","score":0.44678133726119995},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.44036465883255005},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.26931095123291016},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07539084553718567}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8347021341323853},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.7805272340774536},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6799356341362},{"id":"https://openalex.org/C30038468","wikidata":"https://www.wikidata.org/wiki/Q4354775","display_name":"Memorization","level":2,"score":0.6555300951004028},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.6203139424324036},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5995208621025085},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5969004034996033},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.5730674266815186},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5327489376068115},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5299951434135437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5266321301460266},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5146147012710571},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5084725618362427},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.5080814361572266},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.47560223937034607},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4685916304588318},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.44678133726119995},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.44036465883255005},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26931095123291016},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07539084553718567},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C145420912","wikidata":"https://www.wikidata.org/wiki/Q853077","display_name":"Mathematics education","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/asru51503.2021.9688109","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asru51503.2021.9688109","pdf_url":null,"source":{"id":"https://openalex.org/S4363606113","display_name":"2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2109.05092","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2109.05092","pdf_url":"https://arxiv.org/pdf/2109.05092","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:3200311007","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2109.05092","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2109.05092","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2109.05092","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2109.05092","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2109.05092","pdf_url":"https://arxiv.org/pdf/2109.05092","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3200311007.pdf","grobid_xml":"https://content.openalex.org/works/W3200311007.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W2593864460","https://openalex.org/W2810084418","https://openalex.org/W2891628540","https://openalex.org/W2916392228","https://openalex.org/W2916997151","https://openalex.org/W2963250244","https://openalex.org/W2963403868","https://openalex.org/W2995154514","https://openalex.org/W3015752032","https://openalex.org/W3016256870","https://openalex.org/W3045571807","https://openalex.org/W3046177490","https://openalex.org/W3093312917","https://openalex.org/W3093579165","https://openalex.org/W3094965760","https://openalex.org/W3126425262","https://openalex.org/W3160525311","https://openalex.org/W3160789530","https://openalex.org/W3161127962","https://openalex.org/W3161860537","https://openalex.org/W3173051858","https://openalex.org/W3197285286","https://openalex.org/W3197688480","https://openalex.org/W6734897383","https://openalex.org/W6783813245","https://openalex.org/W6784637704"],"related_works":["https://openalex.org/W3010917970","https://openalex.org/W3160523328","https://openalex.org/W3003809177","https://openalex.org/W1576787462","https://openalex.org/W3016053077","https://openalex.org/W3202576380","https://openalex.org/W1968425736","https://openalex.org/W3083012508","https://openalex.org/W2949174760","https://openalex.org/W2397078722","https://openalex.org/W17921661","https://openalex.org/W3160557590","https://openalex.org/W2080141381","https://openalex.org/W3134787422","https://openalex.org/W2899439440","https://openalex.org/W2294401160","https://openalex.org/W1520413003","https://openalex.org/W2142222482","https://openalex.org/W2980849940","https://openalex.org/W2103888789"],"abstract_inverted_index":{"Accurate":[0],"recognition":[1,16],"of":[2,22,170,191,196],"slot":[3,64,149],"values":[4],"such":[5,39,80,151],"as":[6,40,152],"domain":[7,44,53],"specific":[8,54],"words":[9],"or":[10,55],"named":[11],"entities":[12,104,150,180],"by":[13,114],"automatic":[14],"speech":[15],"(ASR)":[17],"systems":[18,47,67],"forms":[19],"the":[20,23,182],"core":[21],"Goal-oriented":[24],"Dialogue":[25],"Systems.":[26],"Although":[27],"it":[28,69],"is":[29,70],"a":[30,117,167,187],"critical":[31],"step":[32],"with":[33,63,129],"direct":[34],"impact":[35],"on":[36,52,142,177,193],"downstream":[37],"tasks":[38],"language":[41],"understanding,":[42],"many":[43],"agnostic":[45],"ASR":[46],"tend":[48],"to":[49,77,126],"perform":[50],"poorly":[51],"long":[56,147],"tail":[57,148],"words.":[58,83],"They":[59],"are":[60],"often":[61,71],"supplemented":[62],"error":[65,111,163,174],"correcting":[66],"but":[68],"hard":[72],"for":[73],"any":[74],"neural":[75],"model":[76,128,165],"directly":[78],"output":[79],"rare":[81,178],"entity":[82],"To":[84],"address":[85],"this":[86],"problem,":[87],"we":[88],"propose":[89],"<tex":[90,96,130],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[91,97,131],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$k$</tex>":[92,98,132],"-nearest":[93],"neighbor":[94],"(":[95],"-NN)":[99],"search":[100,134],"that":[101],"outputs":[102],"domain-specific":[103],"from":[105],"an":[106,194],"explicit":[107],"datastore.":[108],"We":[109,137],"improve":[110],"correction":[112,164],"rate":[113,175],"conveniently":[115],"augmenting":[116],"pretrained":[118],"joint":[119],"phoneme":[120],"and":[121,184],"text":[122],"based":[123],"transformer":[124],"sequence":[125,127],"-NN":[133],"during":[135],"inference.":[136],"evaluate":[138],"our":[139],"proposed":[140],"approach":[141],"five":[143],"different":[144],"domains":[145],"containing":[146],"full":[153],"names,":[154,157],"airports,":[155],"street":[156],"cities,":[158],"states.":[159],"Our":[160],"best":[161],"performing":[162],"shows":[166],"relative":[168,188],"improvement":[169,190],"7.4%":[171],"in":[172],"word":[173,179],"(WER)":[176],"over":[181],"baseline":[183],"also":[185],"achieves":[186],"WER":[189],"9.8%":[192],"out":[195],"vocabulary":[197],"(OOV)":[198],"test":[199],"set.":[200]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-11T14:59:36.786465","created_date":"2025-10-10T00:00:00"}
