Johannes Kiesel, Arefeh Bahrami, Benno Stein, Avishek Anand, Matthias Hagen
{"title":"Clarifying False Memories in Voice-based Search","authors":"Johannes Kiesel, Arefeh Bahrami, Benno Stein, Avishek Anand, Matthias Hagen","doi":"10.1145/3295750.3298961","DOIUrl":null,"url":null,"abstract":"Queries containing false memories (i.e., attributes the user misremembered about a searched item) represent a challenge for search systems. A query with a false memory will match inadequate results or even no result, and an automatic query correction is necessary to satisfy the user expectations. For voice-based search interfaces, which aim at a natural, dialog-based search experience, a sensible answer to this kind of unintentionally ill-posed queries is even more crucial. However, the usual solutions in display-based interfaces for queries without matches (e.g., suggesting to drop some query terms) cannot really be transferred to the voice-based setting. Based on the assumption that false memory queries could be identified---a research problem in its own right---, we present the first user study on how voice-based search systems may communicate the respective corrections to a user. Our study compares the user satisfaction in a voice-based search setting for three kinds of false memory clarifications and a baseline case where the system just answers \"I don't know.'' Our findings suggest that (1)~users are more satisfied when they receive a clarification that and how the system corrected a false memory, (2)~users even prefer failed correction attempts over no such attempt, and (3)~the tone of the clarification has to be considered for the best possible user satisfaction as well.","PeriodicalId":187771,"journal":{"name":"Proceedings of the 2019 Conference on Human Information Interaction and Retrieval","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 Conference on Human Information Interaction and Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3295750.3298961","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Queries containing false memories (i.e., attributes the user misremembered about a searched item) represent a challenge for search systems. A query with a false memory will match inadequate results or even no result, and an automatic query correction is necessary to satisfy the user expectations. For voice-based search interfaces, which aim at a natural, dialog-based search experience, a sensible answer to this kind of unintentionally ill-posed queries is even more crucial. However, the usual solutions in display-based interfaces for queries without matches (e.g., suggesting to drop some query terms) cannot really be transferred to the voice-based setting. Based on the assumption that false memory queries could be identified---a research problem in its own right---, we present the first user study on how voice-based search systems may communicate the respective corrections to a user. Our study compares the user satisfaction in a voice-based search setting for three kinds of false memory clarifications and a baseline case where the system just answers "I don't know.'' Our findings suggest that (1)~users are more satisfied when they receive a clarification that and how the system corrected a false memory, (2)~users even prefer failed correction attempts over no such attempt, and (3)~the tone of the clarification has to be considered for the best possible user satisfaction as well.