{"id":"https://openalex.org/W4221152648","doi":"https://doi.org/10.1109/icassp43922.2022.9746823","title":"Knowledge Augmented Bert Mutual Network in Multi-Turn Spoken Dialogues","display_name":"Knowledge Augmented Bert Mutual Network in Multi-Turn Spoken Dialogues","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4221152648","doi":"https://doi.org/10.1109/icassp43922.2022.9746823"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9746823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746823","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2202.11299","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114858810","display_name":"Ting-Wei Wu","orcid":"https://orcid.org/0000-0002-4927-653X"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ting-Wei Wu","raw_affiliation_strings":["Georgia Institute of Technology,Department of Electrical and Computer Engineering","Department of Electrical and Computer Engineering, Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110122094","display_name":"Biing-Hwang Juang","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Biing-Hwang Juang","raw_affiliation_strings":["Georgia Institute of Technology,Department of Electrical and Computer Engineering","Department of Electrical and Computer Engineering, Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology,Department of Electrical and Computer Engineering","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":0.8435,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.73212906,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"30","issue":null,"first_page":"7487","last_page":"7491"},"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/T12031","display_name":"Speech and dialogue systems","score":0.9990000128746033,"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":0.8322052359580994},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.718172013759613},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5530090928077698},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.5452462434768677},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4719366729259491},{"id":"https://openalex.org/keywords/spoken-language","display_name":"Spoken language","score":0.4659992456436157},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4327501356601715}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8322052359580994},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.718172013759613},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5530090928077698},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.5452462434768677},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4719366729259491},{"id":"https://openalex.org/C2776230583","wikidata":"https://www.wikidata.org/wiki/Q1322198","display_name":"Spoken language","level":2,"score":0.4659992456436157},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4327501356601715},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icassp43922.2022.9746823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9746823","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2202.11299","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2202.11299","pdf_url":"https://arxiv.org/pdf/2202.11299","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2202.11299","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2202.11299","pdf_url":"https://arxiv.org/pdf/2202.11299","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2127795553","https://openalex.org/W2166293310","https://openalex.org/W2172286725","https://openalex.org/W2772831594","https://openalex.org/W2804945011","https://openalex.org/W2884814595","https://openalex.org/W2896457183","https://openalex.org/W2946085385","https://openalex.org/W2963974889","https://openalex.org/W2970676059","https://openalex.org/W2971167298","https://openalex.org/W2997771882","https://openalex.org/W3008915885","https://openalex.org/W3104777900","https://openalex.org/W3122866338","https://openalex.org/W3162752524","https://openalex.org/W3171708917","https://openalex.org/W3174836139","https://openalex.org/W3197269227","https://openalex.org/W3198875375","https://openalex.org/W3211343852","https://openalex.org/W4239008634","https://openalex.org/W4385245566","https://openalex.org/W6678830454","https://openalex.org/W6739901393","https://openalex.org/W6753556266","https://openalex.org/W6755207826","https://openalex.org/W6767311106","https://openalex.org/W6767994401","https://openalex.org/W6784129682","https://openalex.org/W6788825473"],"related_works":["https://openalex.org/W2616627668","https://openalex.org/W3137121595","https://openalex.org/W2787993192","https://openalex.org/W2158269427","https://openalex.org/W4381280689","https://openalex.org/W2847365777","https://openalex.org/W2051345519","https://openalex.org/W2102157173","https://openalex.org/W4382791734","https://openalex.org/W2104168095"],"abstract_inverted_index":{"Modern":[0],"spoken":[1],"language":[2],"understanding":[3],"(SLU)":[4],"systems":[5],"rely":[6],"on":[7,41],"sophisticated":[8],"semantic":[9,52],"notions":[10],"revealed":[11],"in":[12,33,101],"single":[13],"utterances":[14],"to":[15,62,73,88,95],"detect":[16],"intents":[17],"and":[18,94,118],"slots.":[19],"However,":[20],"they":[21],"lack":[22],"the":[23],"capability":[24],"of":[25],"modeling":[26,111],"multi-turn":[27,104],"dynamics":[28],"within":[29,45],"a":[30,46,64,69],"dialogue":[31,55,76,105,119],"particularly":[32],"long-term":[34],"slot":[35],"contexts.":[36],"Without":[37],"external":[38],"knowledge,":[39],"depending":[40],"limited":[42],"linguistic":[43],"legitimacy":[44],"word":[47],"sequence":[48],"may":[49],"overlook":[50],"deep":[51],"information":[53],"across":[54],"turns.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60],"propose":[61],"equip":[63],"BERT-based":[65],"joint":[66],"model":[67],"with":[68,115,127],"knowledge":[70,92,117],"attention":[71],"module":[72],"mutually":[74,110],"leverage":[75],"contexts":[77],"between":[78],"two":[79,102,112],"SLU":[80,113],"tasks.":[81],"A":[82],"gating":[83],"mechanism":[84],"is":[85],"further":[86],"utilized":[87],"filter":[89],"out":[90],"irrelevant":[91],"triples":[93],"circumvent":[96],"distracting":[97],"comprehension.":[98],"Experimental":[99],"results":[100],"complicated":[103],"datasets":[106],"have":[107],"demonstrate":[108],"by":[109],"tasks":[114],"filtered":[116],"contexts,":[120],"our":[121],"approach":[122],"has":[123],"considerable":[124],"improvements":[125],"compared":[126],"several":[128],"competitive":[129],"baselines.":[130]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}
