{"id":"https://openalex.org/W2798968609","doi":"https://doi.org/10.18653/v1/p18-2068","title":"Improving Slot Filling in Spoken Language Understanding with Joint Pointer and Attention","display_name":"Improving Slot Filling in Spoken Language Understanding with Joint Pointer and Attention","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2798968609","doi":"https://doi.org/10.18653/v1/p18-2068","mag":"2798968609"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p18-2068","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-2068","pdf_url":"https://www.aclweb.org/anthology/P18-2068.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P18-2068.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110190620","display_name":"Lin Zhao","orcid":"https://orcid.org/0000-0003-0245-8413"},"institutions":[{"id":"https://openalex.org/I4210120115","display_name":"Robert Bosch (United States)","ror":"https://ror.org/02venad53","country_code":"US","type":"company","lineage":["https://openalex.org/I4210120115","https://openalex.org/I889804353"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lin Zhao","raw_affiliation_strings":["Bosch Research and Technology Center Sunnyvale, CA 94085, USA"],"affiliations":[{"raw_affiliation_string":"Bosch Research and Technology Center Sunnyvale, CA 94085, USA","institution_ids":["https://openalex.org/I4210120115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063460883","display_name":"Zhe Feng","orcid":"https://orcid.org/0000-0001-6036-375X"},"institutions":[{"id":"https://openalex.org/I4210120115","display_name":"Robert Bosch (United States)","ror":"https://ror.org/02venad53","country_code":"US","type":"company","lineage":["https://openalex.org/I4210120115","https://openalex.org/I889804353"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhe Feng","raw_affiliation_strings":["Bosch Research and Technology Center Sunnyvale, CA 94085, USA"],"affiliations":[{"raw_affiliation_string":"Bosch Research and Technology Center Sunnyvale, CA 94085, USA","institution_ids":["https://openalex.org/I4210120115"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5110190620"],"corresponding_institution_ids":["https://openalex.org/I4210120115"],"apc_list":null,"apc_paid":null,"fwci":5.4048,"has_fulltext":true,"cited_by_count":52,"citation_normalized_percentile":{"value":0.96468269,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"426","last_page":"431"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9994000196456909,"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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8503464460372925},{"id":"https://openalex.org/keywords/pointer","display_name":"Pointer (user interface)","score":0.8150357604026794},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.7296699285507202},{"id":"https://openalex.org/keywords/spoken-language","display_name":"Spoken language","score":0.6135032176971436},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.5882117748260498},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5625154376029968},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.561665415763855},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5389485955238342},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5386829376220703},{"id":"https://openalex.org/keywords/filling-in","display_name":"Filling-in","score":0.5020058155059814},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.48246484994888306},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.47045838832855225},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.441580593585968},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43529051542282104},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4107290506362915},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1301717460155487}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8503464460372925},{"id":"https://openalex.org/C150202949","wikidata":"https://www.wikidata.org/wiki/Q107602","display_name":"Pointer (user interface)","level":2,"score":0.8150357604026794},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.7296699285507202},{"id":"https://openalex.org/C2776230583","wikidata":"https://www.wikidata.org/wiki/Q1322198","display_name":"Spoken language","level":2,"score":0.6135032176971436},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.5882117748260498},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5625154376029968},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.561665415763855},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5389485955238342},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5386829376220703},{"id":"https://openalex.org/C200873422","wikidata":"https://www.wikidata.org/wiki/Q5448821","display_name":"Filling-in","level":2,"score":0.5020058155059814},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.48246484994888306},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.47045838832855225},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.441580593585968},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43529051542282104},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4107290506362915},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1301717460155487},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p18-2068","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-2068","pdf_url":"https://www.aclweb.org/anthology/P18-2068.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p18-2068","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p18-2068","pdf_url":"https://www.aclweb.org/anthology/P18-2068.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2798968609.pdf","grobid_xml":"https://content.openalex.org/works/W2798968609.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1632484548","https://openalex.org/W1989996186","https://openalex.org/W2077302143","https://openalex.org/W2133564696","https://openalex.org/W2137871902","https://openalex.org/W2157331557","https://openalex.org/W2160200434","https://openalex.org/W2166293310","https://openalex.org/W2251058040","https://openalex.org/W2251355666","https://openalex.org/W2400801499","https://openalex.org/W2507756961","https://openalex.org/W2516930406","https://openalex.org/W2534381863","https://openalex.org/W2606974598","https://openalex.org/W2740107682","https://openalex.org/W2951222182","https://openalex.org/W2963369167","https://openalex.org/W2964121744","https://openalex.org/W2964308564"],"related_works":["https://openalex.org/W2529301793","https://openalex.org/W2384121599","https://openalex.org/W2038083449","https://openalex.org/W2562096895","https://openalex.org/W2333799855","https://openalex.org/W3177678247","https://openalex.org/W1999617572","https://openalex.org/W2944572343","https://openalex.org/W2351687372","https://openalex.org/W2284708545"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,12,18,46,58,63,96],"generative":[3],"neural":[4],"network":[5],"model":[6,15,37,94],"for":[7],"slot":[8,27,39,80],"filling":[9,81],"based":[10],"on":[11,106],"sequenceto-sequence":[13],"(Seq2Seq)":[14],"together":[16],"with":[17],"pointer":[19,59],"network,":[20,60],"in":[21,31],"the":[22,32,66,76,86,92,103,107],"situation":[23],"where":[24],"only":[25],"sentence-level":[26],"annotations":[28],"are":[29],"available":[30],"spoken":[33,97],"dialogue":[34],"data.":[35,109],"This":[36],"predicts":[38],"values":[40],"by":[41],"jointly":[42],"learning":[43],"to":[44],"copy":[45],"word":[47,64],"which":[48],"may":[49],"be":[50],"out-of-vocabulary":[51],"(OOV)":[52],"from":[53],"an":[54,69],"input":[55],"utterance":[56],"through":[57,68],"or":[61],"generate":[62],"within":[65],"vocabulary":[67],"attentional":[70],"Seq2Seq":[71],"model.":[72],"Experimental":[73],"results":[74],"show":[75],"effectiveness":[77],"of":[78],"our":[79],"model,":[82],"especially":[83],"at":[84],"addressing":[85],"OOV":[87],"problem.":[88],"Additionally,":[89],"we":[90],"integrate":[91],"proposed":[93],"into":[95],"language":[98],"understanding":[99],"system":[100],"and":[101],"achieve":[102],"state-of-the-art":[104],"performance":[105],"benchmark":[108]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":8}],"updated_date":"2026-03-01T06:05:34.837733","created_date":"2025-10-10T00:00:00"}