{"id":"https://openalex.org/W2473965551","doi":"https://doi.org/10.21437/interspeech.2016-312","title":"End-to-End Memory Networks with Knowledge Carryover for Multi-Turn Spoken Language Understanding","display_name":"End-to-End Memory Networks with Knowledge Carryover for Multi-Turn Spoken Language Understanding","publication_year":2016,"publication_date":"2016-08-28","ids":{"openalex":"https://openalex.org/W2473965551","doi":"https://doi.org/10.21437/interspeech.2016-312","mag":"2473965551"},"language":"en","primary_location":{"id":"doi:10.21437/interspeech.2016-312","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2016-312","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2016","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/A5076610826","display_name":"Yun-Nung Chen","orcid":"https://orcid.org/0000-0003-1777-3942"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yun-Nung Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068709817","display_name":"Dilek Hakkani\u2010T\u00fcr","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dilek Hakkani-T\u00fcr","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087941479","display_name":"G\u00f6khan T\u00fcr","orcid":"https://orcid.org/0009-0008-7740-2557"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gokhan Tur","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114910293","display_name":"Jianfeng Gao","orcid":"https://orcid.org/0000-0002-5702-6143"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianfeng Gao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100671324","display_name":"Li Deng","orcid":"https://orcid.org/0000-0002-1014-0790"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li Deng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":161,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3245","last_page":"3249"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10028","display_name":"Topic Modeling","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"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9976000189781189,"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":0.8298763036727905},{"id":"https://openalex.org/keywords/spoken-language","display_name":"Spoken language","score":0.6889106631278992},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6628957986831665},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.6246922612190247},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5289739966392517},{"id":"https://openalex.org/keywords/turn-taking","display_name":"Turn-taking","score":0.4924372136592865},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4652501046657562},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.45666933059692383},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43086376786231995},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42908942699432373},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3607980012893677},{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.2469061017036438},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.14708364009857178},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.14135384559631348},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09085622429847717}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8298763036727905},{"id":"https://openalex.org/C2776230583","wikidata":"https://www.wikidata.org/wiki/Q1322198","display_name":"Spoken language","level":2,"score":0.6889106631278992},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6628957986831665},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.6246922612190247},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5289739966392517},{"id":"https://openalex.org/C2776352735","wikidata":"https://www.wikidata.org/wiki/Q2313343","display_name":"Turn-taking","level":3,"score":0.4924372136592865},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4652501046657562},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.45666933059692383},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43086376786231995},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42908942699432373},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3607980012893677},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.2469061017036438},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.14708364009857178},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.14135384559631348},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09085622429847717},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21437/interspeech.2016-312","is_oa":false,"landing_page_url":"https://doi.org/10.21437/interspeech.2016-312","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Interspeech 2016","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W581956982","https://openalex.org/W648947103","https://openalex.org/W1550863320","https://openalex.org/W1551803577","https://openalex.org/W1793121960","https://openalex.org/W1924770834","https://openalex.org/W1964812476","https://openalex.org/W1972595521","https://openalex.org/W2004672974","https://openalex.org/W2024632416","https://openalex.org/W2064675550","https://openalex.org/W2086342113","https://openalex.org/W2094472029","https://openalex.org/W2106347453","https://openalex.org/W2110485445","https://openalex.org/W2124895976","https://openalex.org/W2129554061","https://openalex.org/W2130942839","https://openalex.org/W2137871902","https://openalex.org/W2143612262","https://openalex.org/W2153962611","https://openalex.org/W2166293310","https://openalex.org/W2167839676","https://openalex.org/W2170919426","https://openalex.org/W2252022287","https://openalex.org/W2274861244","https://openalex.org/W2335262272","https://openalex.org/W2400801499","https://openalex.org/W2405622356","https://openalex.org/W2473329891","https://openalex.org/W2964121744","https://openalex.org/W2964199361","https://openalex.org/W2964308564","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2529301793","https://openalex.org/W1978877097","https://openalex.org/W2903456225","https://openalex.org/W2284708545","https://openalex.org/W3208962307","https://openalex.org/W2595453317","https://openalex.org/W3182597358","https://openalex.org/W2558461613","https://openalex.org/W2399858921","https://openalex.org/W2358842429"],"abstract_inverted_index":{"Spoken":[0],"language":[1],"understanding":[2],"(SLU)":[3],"is":[4],"a":[5,9],"core":[6],"component":[7,22],"of":[8,17,27,61],"spoken":[10],"dialogue":[11,18],"system.":[12],"In":[13],"the":[14,20,32,36,40,59,62,69,77,83,114,117,145,160,165,168],"traditional":[15],"architecture":[16,89,149],"systems,":[19],"SLU":[21],"treats":[23],"each":[24,28],"utterance":[25],"independent":[26],"other,":[29],"and":[30,56,106,116,132,163],"then":[31,57],"following":[33],"components":[34],"aggregate":[35],"multi-turn":[37,99,161],"information":[38],"in":[39,68,98,113,159],"separate":[41],"phases.":[42],"However,":[43],"there":[44],"are":[45],"two":[46],"challenges:":[47],"1)":[48],"errors":[49],"from":[50],"previous":[51],"turns":[52],"may":[53,72],"be":[54,74,109],"propagated":[55],"degrade":[58],"performance":[60],"current":[63,78],"turn;":[64],"2)":[65],"knowledge":[66,96,157],"mentioned":[67],"long":[70],"history":[71],"not":[73],"carried":[75],"into":[76],"turn.":[79],"This":[80],"paper":[81],"addresses":[82],"above":[84],"issues":[85],"by":[86],"proposing":[87],"an":[88,121],"using":[90,167],"end-to-end":[91],"memory":[92,115,147],"networks":[93],"to":[94,124],"model":[95,123],"carryover":[97,158],"conversations,":[100],"where":[101],"utterances":[102],"encoded":[103],"with":[104],"intents":[105],"slots":[107],"can":[108,150],"stored":[110,127],"as":[111],"embeddings":[112],"decoding":[118],"phase":[119],"applies":[120],"attention":[122],"leverage":[125],"previously":[126],"semantics":[128,154],"for":[129,155,176],"intent":[130],"prediction":[131],"slot":[133],"tagging":[134],"simultaneously.":[135],"The":[136],"experiments":[137],"on":[138],"Microsoft":[139],"Cortana":[140],"conversational":[141],"data":[142],"show":[143],"that":[144],"proposed":[146],"network":[148,172],"effectively":[151],"extract":[152],"salient":[153],"modeling":[156],"conversations":[162],"outperform":[164],"results":[166],"state-of-the-art":[169],"recurrent":[170],"neural":[171],"framework":[173],"(RNN)":[174],"designed":[175],"single-turn":[177],"SLU.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":27},{"year":2020,"cited_by_count":18},{"year":2019,"cited_by_count":41},{"year":2018,"cited_by_count":30},{"year":2017,"cited_by_count":20},{"year":2016,"cited_by_count":7}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}