{"title":"多模态虚拟客服代理的用户行为分析","authors":"Ian Beaver, Cynthia Freeman","doi":"10.1109/SLT.2016.7846322","DOIUrl":null,"url":null,"abstract":"We investigate the occurrence of user restatement when there is no apparent error in Intelligent Virtual Assistant (IVA) understanding in a multimodal customer service environment. We define several classes of response medium combinations and use various statistical measures to determine how the combination of medium and linguistic complexity impacts the user's apparent willingness to accept their query result. Through analysis on 3; 000 sessions with a live customer service IVA deployed on an airline company website and mobile application, we discover that as more media are involved in a response, user restatements increase. We also determine which linguistic complexity measures should be minimized for every response class in order to improve user comprehension.","PeriodicalId":281635,"journal":{"name":"2016 IEEE Spoken Language Technology Workshop (SLT)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Analysis of user behavior with multimodal virtual customer service agents\",\"authors\":\"Ian Beaver, Cynthia Freeman\",\"doi\":\"10.1109/SLT.2016.7846322\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We investigate the occurrence of user restatement when there is no apparent error in Intelligent Virtual Assistant (IVA) understanding in a multimodal customer service environment. We define several classes of response medium combinations and use various statistical measures to determine how the combination of medium and linguistic complexity impacts the user's apparent willingness to accept their query result. Through analysis on 3; 000 sessions with a live customer service IVA deployed on an airline company website and mobile application, we discover that as more media are involved in a response, user restatements increase. We also determine which linguistic complexity measures should be minimized for every response class in order to improve user comprehension.\",\"PeriodicalId\":281635,\"journal\":{\"name\":\"2016 IEEE Spoken Language Technology Workshop (SLT)\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Spoken Language Technology Workshop (SLT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SLT.2016.7846322\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Spoken Language Technology Workshop (SLT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SLT.2016.7846322","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of user behavior with multimodal virtual customer service agents
We investigate the occurrence of user restatement when there is no apparent error in Intelligent Virtual Assistant (IVA) understanding in a multimodal customer service environment. We define several classes of response medium combinations and use various statistical measures to determine how the combination of medium and linguistic complexity impacts the user's apparent willingness to accept their query result. Through analysis on 3; 000 sessions with a live customer service IVA deployed on an airline company website and mobile application, we discover that as more media are involved in a response, user restatements increase. We also determine which linguistic complexity measures should be minimized for every response class in order to improve user comprehension.
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