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abstract

Learnability through Adaptive Discovery Tools in Voice User Interfaces

Authors:

Anushay Furqan,

Jichen ZhuAuthors Info & Claims

CHI EA '17: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems

Pages 1617 - 1623

https://doi.org/10.1145/3027063.3053166

Published: 06 May 2017 Publication 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.

References

[1]

Ken Abbott. 2002. VUI Design Principles and Techniques. Apress, Berkeley, CA, 87--103.

[2]

Pierre A. Akiki, Arosha K. Bandara, and Yijun Yu. 2014. Adaptive Model-Driven User Interface Development Systems. ACM Comput. Surv. 47, 1, Article 9 (May 2014), 33 pages.

[3]

Jonatan Andersson. 2016. Assessment and Improvement of Initial Learnability in Complex Systems: A Qualitative Study to Promote Intuitive Software Development. (2016).

[4]

Virginia Braun and Victoria Clarke. 2006. Using thematic analysis in psychology. Qualitative research in psychology 3, 2 (2006), 77--101.

[5]

Dermot Browne. 2016. Adaptive User Interfaces. Elsevier Science.

[6]

Fang Chen. 2006. Designing Human Interface in Speech Technology. Springer US.

[7]

Eric Corbett and Astrid Weber. 2016. What Can I Say?: Addressing User Experience Challenges of a Mobile Voice User Interface for Accessibility. In Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI '16). ACM, New York, NY, USA, 72--82.

Digital Library

[8]

Tovi Grossman, George Fitzmaurice, and Ramtin Attar. 2009. A Survey of Software Learnability: Metrics, Methodologies and Guidelines. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '09). ACM, New York, NY, USA, 649--658.

Digital Library

[9]

Jonathan Huyghe, Jan Derboven, and Dirk De Grooff. 2014. ALADIN: Demo of a Multimodal Adaptive Voice Interface. In Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational (NordiCHI '14). ACM, New York, NY, USA, 1035--1038.

Digital Library

[10]

Candace A Kamm, Diane J Litman, and Marilyn A Walker. 1998. From novice to expert: the effect of tutorials on user expertise with spoken dialogue systems. In ICSLP. Citeseer.

[11]

Laura Klein. 2015. Design for Voice Interfaces. O'Reilly Media, Sebastopol, CA.

[12]

Kazunori Komatani, Shinichi Ueno, Tatsuya Kawahara, and Hiroshi G. Okuno. 2005. User Modeling in Spoken Dialogue Systems to Generate Flexible Guidance. User Modeling and User-Adapted Interaction 15, 1 (2005), 169--183.

Digital Library

[13]

Carolina Milanesi. 2016. Voice Assistant Anyone? Yes please, but not in public! (June 2016). http://creativestrategies.com/ voice-assistant-anyone-yes-please-but-not-in-public/

[14]

Jakob Nielsen. 2000. Why You Only Need to Test with 5 Users. (March 2000). https://www.nngroup.com/articles/ why-you-only-need-to-test-with-5-users/

[15]

Daniel O'Sullivan. 2009. Using an Adaptive Voice User Interface to Gain Efficiencies in Automated Calls. Technical Report. Contact Solutions | Inventing Real Customer Service, Smithtown, USA.

[16]

Qian Yang, John Zimmerman, Aaron Steinfeld, and Anthony Tomasic. 2016. Planning Adaptive Mobile Experiences When Wireframing. In Proceedings of the 2016 ACM Conference on Designing Interactive Systems (DIS '16). ACM, New York, NY, USA, 565--576.

Digital Library

[17]

Yu Zhong, T. V. Raman, Casey Burkhardt, Fadi Biadsy, and Jeffrey P. Bigham. 2014. JustSpeak: Enabling Universal Voice Control on Android. In Proceedings of the 11th Web for All Conference (W4A '14). ACM, New York, NY, USA, Article 36, 4 pages.

Cited By

Doi TNishikawa Y(2024)Usability Analysis of Smart Speakers from a Learnability Perspective for Novel UsersApplied System Innovation10.3390/asi70300367:3(36)Online publication date: 25-Apr-2024
https://doi.org/10.3390/asi7030036
Do HBrachman MDugan CJohnson JLauer JRai PPan Q(2024)Grounding with Structure: Exploring Design Variations of Grounded Human-AI Collaboration in a Natural Language InterfaceProceedings of the ACM on Human-Computer Interaction10.1145/36869028:CSCW2(1-27)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686902
Tran NDeVries PSeita MKushalnagar RGlasser AVogler C(2024)Assessment of Sign Language-Based versus Touch-Based Input for Deaf Users Interacting with Intelligent Personal AssistantsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642094(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642094
Show More Cited By

Index Terms

Learnability through Adaptive Discovery Tools in Voice User Interfaces
1. Human-centered computing
  1. Human computer interaction (HCI)

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Information & Contributors

Information

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

General Chairs:
Gloria Mark
University of California Irvine
,
Susan Fussell
Cornell University
,
Program Chairs:
Cliff Lampe
University of Michigan
,
m.c. schraefel
University of Southampton
,
Juan Pablo Hourcade
University of Iowa
,
Caroline Appert
Université Paris-Sud
,
Daniel Wigdor
University of Toronto

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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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 May 2017

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CHI '17

Sponsor:

SIGCHI

CHI '17: CHI Conference on Human Factors in Computing Systems

May 6 - 11, 2017

Colorado, Denver, USA

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CHI EA '17 Paper Acceptance Rate 1,000 of 5,000 submissions, 20%;

Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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CHI 2025

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sigchi

ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

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Citations

Cited By

Doi TNishikawa Y(2024)Usability Analysis of Smart Speakers from a Learnability Perspective for Novel UsersApplied System Innovation10.3390/asi70300367:3(36)Online publication date: 25-Apr-2024
https://doi.org/10.3390/asi7030036
Do HBrachman MDugan CJohnson JLauer JRai PPan Q(2024)Grounding with Structure: Exploring Design Variations of Grounded Human-AI Collaboration in a Natural Language InterfaceProceedings of the ACM on Human-Computer Interaction10.1145/36869028:CSCW2(1-27)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686902
Tran NDeVries PSeita MKushalnagar RGlasser AVogler C(2024)Assessment of Sign Language-Based versus Touch-Based Input for Deaf Users Interacting with Intelligent Personal AssistantsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642094(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642094
Mackamul ECasiez GMalacria S(2024)Clarifying and differentiating discoverabilityHuman–Computer Interaction10.1080/07370024.2024.2364606(1-26)Online publication date: 13-Jun-2024
https://doi.org/10.1080/07370024.2024.2364606
Vu MWang HLi ZHaffari GXing ZChen C(2023)Voicify Your UIProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35819987:1(1-22)Online publication date: 28-Mar-2023
https://dl.acm.org/doi/10.1145/3581998
Brachman MPan QDo HDugan CChaudhary AJohnson JRai PChakraborti TGschwind TLaredo JMiksovic CScotton PTalamadupula KThomas G(2023)Follow the Successful Herd: Towards Explanations for Improved Use and Mental Models of Natural Language SystemsProceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581641.3584088(220-239)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3581641.3584088
Murad CCandello HMunteanu C(2023)What’s The Talk on VUI Guidelines? A Meta-Analysis of Guidelines for Voice User Interface DesignProceedings of the 5th International Conference on Conversational User Interfaces10.1145/3571884.3597129(1-16)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3571884.3597129
Meck ADraxler CVogt T(2023)Failing with Grace: Exploring the Role of Repair Costs in Conversational Breakdowns with in-Car Voice AssistantsInternational Journal of Human–Computer Interaction10.1080/10447318.2023.226679140:22(7574-7592)Online publication date: 11-Oct-2023
https://doi.org/10.1080/10447318.2023.2266791
Murad CTasnim HMunteanu C(2022)“Voice-First Interfaces in a GUI-First Design World”: Barriers and Opportunities to Supporting VUI Designers On-the-JobProceedings of the 4th Conference on Conversational User Interfaces10.1145/3543829.3543842(1-10)Online publication date: 26-Jul-2022
https://dl.acm.org/doi/10.1145/3543829.3543842
Kim TChoi DChoi YKim J(2022)Stylette: Styling the Web with Natural LanguageProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501931(1-17)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3501931
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