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Learnability through Adaptive Discovery Tools in Voice User Interfaces

Published:06 May 2017Publication History

ABSTRACT

The invisible nature of VUIs has been attributed to challenging discoverability with VUIs. Low discoverability often leads to learnability issues. Researchers have designed visual tools for VUIs to help users learn as they go. However, few have used adaptation to ensure that learnability with the help of these tools extends beyond initial use. We designed DiscoverCal, a calendar application designed using adaptive discovery tools to improve learnability in VUIs. In this paper, we identify key characteristics of existing discovery tools. We present our design of a VUI that adapts based on contextual relevance and user performance in order to extend learnability beyond initial use. We briefly discuss our user study design.

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    • Published in

      cover image ACM Conferences
      CHI EA '17: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems
      May 2017
      3954 pages
      ISBN:9781450346566
      DOI:10.1145/3027063

      Copyright © 2017 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 6 May 2017

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      CHI EA '17 Paper Acceptance Rate1,000of5,000submissions,20%Overall Acceptance Rate6,164of23,696submissions,26%

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