{"id":"https://openalex.org/W4376852290","doi":"https://doi.org/10.1145/3573942.3573962","title":"Research on the Generation of Emotional Dialogue Statements in Generative Adversarial Networks","display_name":"Research on the Generation of Emotional Dialogue Statements in Generative Adversarial Networks","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4376852290","doi":"https://doi.org/10.1145/3573942.3573962"},"language":"en","primary_location":{"id":"doi:10.1145/3573942.3573962","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3573942.3573962","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3573942.3573962?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3573942.3573962?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016865114","display_name":"Wei Guan","orcid":"https://orcid.org/0000-0001-5832-2027"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Guan","raw_affiliation_strings":["School of Computer Science, Xi'an University of Posts and Telecommunications, Xi'an University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Xi'an University of Posts and Telecommunications, Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110976428","display_name":"Mingrui Huang","orcid":"https://orcid.org/0000-0002-3320-083X"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingrui Huang","raw_affiliation_strings":["School of Computer Science, Xi'an University of Posts and Telecommunications, Xi'an University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Xi'an University of Posts and Telecommunications, Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100606529","display_name":"Li Ma","orcid":"https://orcid.org/0000-0002-4359-0050"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Ma","raw_affiliation_strings":["School of Computer Science, Xi'an University of Posts and Telecommunicationsce, Xi'an University of Posts and Telecommunications, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Xi'an University of Posts and Telecommunicationsce, Xi'an University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5016865114"],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37348579,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2020","issue":null,"first_page":"129","last_page":"136"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.8248999714851379,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13910","display_name":"Computational and Text Analysis Methods","score":0.8248999714851379,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.8119000196456909,"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":0.7208747267723083},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6643387079238892},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.6524503231048584},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6159468293190002},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.611598789691925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6016561985015869},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5910519361495972},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5815811157226562},{"id":"https://openalex.org/keywords/natural-language-generation","display_name":"Natural language generation","score":0.5601187348365784},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.528387725353241},{"id":"https://openalex.org/keywords/emotional-intelligence","display_name":"Emotional intelligence","score":0.5039364695549011},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4887559413909912},{"id":"https://openalex.org/keywords/statement","display_name":"Statement (logic)","score":0.48179930448532104},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.4279518127441406},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.2984144687652588},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.20394617319107056},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1941351294517517},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.08249121904373169}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7208747267723083},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6643387079238892},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.6524503231048584},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6159468293190002},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.611598789691925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6016561985015869},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5910519361495972},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5815811157226562},{"id":"https://openalex.org/C2776187449","wikidata":"https://www.wikidata.org/wiki/Q1513879","display_name":"Natural language generation","level":3,"score":0.5601187348365784},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.528387725353241},{"id":"https://openalex.org/C174107131","wikidata":"https://www.wikidata.org/wiki/Q191591","display_name":"Emotional intelligence","level":2,"score":0.5039364695549011},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4887559413909912},{"id":"https://openalex.org/C2777026412","wikidata":"https://www.wikidata.org/wiki/Q2684591","display_name":"Statement (logic)","level":2,"score":0.48179930448532104},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.4279518127441406},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2984144687652588},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.20394617319107056},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1941351294517517},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.08249121904373169},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3573942.3573962","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3573942.3573962","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3573942.3573962?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3573942.3573962","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3573942.3573962","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3573942.3573962?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6700000166893005,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4376852290.pdf","grobid_xml":"https://content.openalex.org/works/W4376852290.grobid-xml"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W2583741591","https://openalex.org/W2962796276","https://openalex.org/W2963248348","https://openalex.org/W2964268978","https://openalex.org/W3006320604","https://openalex.org/W4231805003","https://openalex.org/W4238747299","https://openalex.org/W4246775161","https://openalex.org/W4252240600"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W2387995142","https://openalex.org/W4380714744","https://openalex.org/W4319453655","https://openalex.org/W2089959425","https://openalex.org/W2057775761","https://openalex.org/W2964074194","https://openalex.org/W2995777218"],"abstract_inverted_index":{"With":[0],"the":[1,20,28,37,49,62,95,112,116,124,130,176,181,190,199,202,213,231,239,243,252,257,269,285],"continuous":[2],"progress":[3],"of":[4,22,30,40,51,115,167,178,183,216,245,264],"neural":[5,24],"network":[6,25,149,158],"technology":[7,26],"in":[8,27,48,76,94,208,222,225,284],"different":[9,207,209],"fields,":[10],"people":[11],"have":[12],"put":[13],"forward":[14],"higher":[15],"requirements":[16],"and":[17,33,69,123,156,162,180,194,212,241,268],"prospects":[18],"for":[19,65,98,261],"research":[21,46,71],"deep":[23],"field":[29,50],"artificial":[31,41],"intelligence,":[32],"language":[34,53],"intelligence":[35],"is":[36,72,119,126,219,266],"core":[38],"problem":[39,200],"intelligence.":[42],"As":[43],"an":[44,139],"important":[45],"content":[47],"natural":[52],"processing,":[54],"dialogue":[55,99,141],"generation":[56,100,142,177,244],"has":[57,159,271],"been":[58,272],"widely":[59,74],"concerned":[60],"by":[61],"academic":[63],"community":[64],"a":[66,146,160],"long":[67],"time,":[68],"this":[70,133],"also":[73],"used":[75],"people's":[77],"daily":[78],"lives,":[79],"such":[80,102],"as":[81,103],"medical":[82],"Q&A,":[83],"e-commerce":[84],"shopping,":[85],"emotional":[86,113,140,154,184,214,232,276],"response,":[87],"etc.":[88],"There":[89],"are":[90,172,235],"still":[91],"many":[92],"problems":[93],"existing":[96],"model":[97,143,270],"research,":[101],"easy":[104],"to":[105,129,137,150,174,186,197,227,238,274],"produce":[106,275],"universal":[107],"replies":[108,179],"(\"ok\",":[109],"\"emm\",":[110],"etc.),":[111],"information":[114,215],"reply":[117,277],"statement":[118],"not":[120,127,220],"strong":[121],"enough,":[122],"response":[125],"related":[128],"subject.":[131],"For":[132],"problem,":[134],"we":[135],"propose":[136],"use":[138],"based":[144],"on":[145],"generative":[147,254],"adversarial":[148,255],"generate":[151],"statements":[152,278],"with":[153,251,279],"responses,":[155],"our":[157],"generator":[161,240,246],"multi-level":[163,169],"discriminator.":[164],"In":[165,248],"terms":[166],"discriminators,":[168],"discourse":[170],"discriminators":[171],"introduced":[173],"guide":[175,242],"strengthening":[182],"information,":[185],"discriminate":[187],"emotions":[188],"at":[189],"individual":[191],"word":[192],"level":[193],"sentence":[195],"level,":[196],"solve":[198],"that":[201],"same":[203],"text":[204,265],"may":[205],"be":[206],"semantic":[210],"environments":[211],"some":[217,223],"words":[218],"clear":[221],"cases,":[224],"order":[226],"achieve":[228],"maximum":[229],"accuracy":[230],"discrimination":[233],"results":[234],"fed":[236],"back":[237],"statements.":[247],"addition,":[249],"compared":[250],"traditional":[253],"network,":[256],"task":[258],"processing":[259],"ability":[260],"large":[262],"pieces":[263],"improved,":[267],"shown":[273],"better":[280],"baseline":[281],"levels":[282],"than":[283],"past.":[286]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}