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Refactoring the UX of a popular voice application

Published: 22 March 2021 Publication History

Abstract

Commercial voice services like Google Assistant and Amazon Alexa are reaching extreme popularity. While Natural Language Processing (NLP) and Artificial Intelligence (AI) techniques -- applied to the aural channel -- deliver high quality voice recognition, the voice channel still lacks a good methodology to design user experiences. For instance, The Amazon Alexa team suggests gathering the information model of Alexa skills by talking with test users behind a curtain, pretending to be the machine. In our opinion, such kind of bottom-up strategy is not effective because it overfits the UX to very specific cases. A top-down approach could provide the right answer also in unseen and unpredictable situations instead. Our work aims to propose a novel model driven approach that allows authors to design from scratch the overall vocal UX as well as rethink existing visual UX before porting them to the aural channel. Our approach, which is inherently top-down, is based on Aural IDM, an UX design method thought for screen readers modelling in the early '00. In this paper we've refactored the Spotify Alexa skill to demonstrate the validity of Aural IDM for designing vocal UXs. The experience of Spotify on Alexa is quite primordial and does not reflect the richness of the desktop app. A prototype is currently under development, and the result of a comparison between the AS-IS and TO-BE voice skill will be subject of a future work.

References

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Davide Bolchini, Sebastiano Colazzo, Paolo Paolini, and Daniele Vitali. 2006. Designing aural information architectures. In Proceedings of the 24th annual ACM international conference on Design of communication (SIGDOC '06). ACM, New York, NY, USA, 51--58.
[2]
Paul Luff, David Frohlich, and Nigel Gilber (eds.). 1990. Computers and Conversation. Academic Press.
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Cosmin Munteanu and Gerald Penn. 2015. Speech-based Interaction: Myths, Challenges, and Opportunities. In Proceedings of the 20th International Conference on Intelligent User Interfaces (IUI '15). ACM, New York, NY, USA, 437--438.
[4]
Joseph 'Jofish' Kaye, Joel Fischer, Jason Hong, Frank R. Bentley, Cosmin Munteanu, Alexis Hiniker, Janice Y. Tsai, and Tawfiq Ammari. 2018. Panel: Voice Assistants, UX Design and Research. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (CHI EA '18). ACM, New York, NY, USA, Paper panel01, 5 pages.
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Stuart Reeves, Martin Porcheron, Joel E. Fischer, Heloisa Candello, Donald McMillan, Moira McGregor, Robert J. Moore, Rein Sikveland, Alex S. Taylor, Julia Velkovska, and Moustafa Zouinar. 2018. Voice-based Conversational UX Studies and Design. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (CHI EA '18). ACM, New York, NY, USA, Paper W38, 8 pages.
[6]
Robert J. Moore and Raphael Arar. 2019. Conversational UX Design: A Practitioner's Guide to the Natural Conversation Framework. ACM, New York, NY, USA.
[7]
D. Bolchini and P. Paolini, "Interactive dialogue model: a design technique for multichannel applications," in IEEE Transactions on Multimedia, vol. 8, no. 3, pp. 529--541, June 2006.

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cover image ACM Other conferences
ICIST '20: Proceedings of the 10th International Conference on Information Systems and Technologies
June 2020
292 pages
ISBN:9781450376556
DOI:10.1145/3447568
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 March 2021

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Author Tags

  1. Voice assistants
  2. conversational UX design
  3. model-driven design

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