More Web Proxy on the site http://driver.im/

Work in Progress

Are you sure you want to order that?: On Appropriateness of Voice-only Proactive Feedback Strategies

Authors:

Mateusz Dubiel,

Kerstin Bongard-Blanchy,

Anastasia SergeevaAuthors Info & Claims

CUI '23: Proceedings of the 5th International Conference on Conversational User Interfaces

Article No.: 43, Pages 1 - 6

https://doi.org/10.1145/3571884.3604312

Published: 19 July 2023 Publication History

Abstract

Conversational agents (CAs) that deliver proactive interventions can benefit users by reducing their cognitive workload and improving performance. However, little is known regarding how such interventions would impact perception of CA’s appropriateness in voice-only, decision-making tasks. We conducted a within-subjects experiment (N=30) to evaluate the effect of CA’s feedback delivery strategy at three levels (no feedback, unsolicited, and solicited feedback) in an interactive food ordering scenario. We discovered that unsolicited feedback was perceived to be more appropriate than solicited feedback. Our results provide preliminary insights regarding the impact of proactive feedback on CA perception in decision-making tasks.

References

[1]

Tawfiq Ammari, Jofish Kaye, Janice Y Tsai, and Frank Bentley. 2019. Music, Search, and IoT: How People (Really) Use Voice Assistants.ACM Trans. Comput. Hum. Interact. 26, 3 (2019), 17–1.

Digital Library

[2]

Yulia E Chentsova Dutton. 2012. Butting in vs. being a friend: Cultural differences and similarities in the evaluation of imposed social support. J. Soc. Psychol. 152, 4 (2012), 493–509.

[3]

Michael Chourdakis, Thrasivoulos Tzellos, Chryssa Pourzitaki, Konstantinos A Toulis, George Papazisis, and Dimitrios Kouvelas. 2011. Evaluation of dietary habits and assessment of cardiovascular disease risk factors among Greek university students. Appetite 57, 2 (2011), 377–383.

[4]

Leigh Clark, Nadia Pantidi, Orla Cooney, Philip Doyle, Diego Garaialde, Justin Edwards, Brendan Spillane, Emer Gilmartin, Christine Murad, Cosmin Munteanu, 2019. What makes a good conversation? Challenges in designing truly conversational agents. In Proc. CHI. 1–12.

[5]

Nils Dahlbäck, Arne Jönsson, and Lars Ahrenberg. 1993. Wizard of Oz studies—why and how. Knowl Based Syst. 6, 4 (1993), 258–266.

Digital Library

[6]

Janna T Deelstra, Maria CW Peeters, Wilmar B Schaufeli, Wolfgang Stroebe, Fred RH Zijlstra, and Lorenz P Van Doornen. 2003. Receiving instrumental support at work: when help is not welcome.J. Appl. Psychol. 88, 2 (2003), 324.

[7]

Tiffany D Do, Ryan P McMahan, and Pamela J Wisniewski. 2022. A New Uncanny Valley? The Effects of Speech Fidelity and Human Listener Gender on Social Perceptions of a Virtual-Human Speaker. In Proc. CHI. 1–11.

Digital Library

[8]

Philip R Doyle, Justin Edwards, Odile Dumbleton, Leigh Clark, and Benjamin R Cowan. 2019. Mapping perceptions of humanness in intelligent personal assistant interaction. In Proc. MobileHCI. 1–12.

Digital Library

[9]

Mateusz Dubiel, Martin Halvey, Leif Azzopardi, Damien Anderson, and Sylvain Daronnat. 2020. Conversational strategies: impact on search performance in a goal-oriented task. In The Third International Workshop on Conversational Approaches to Information Retrieval.

[10]

Justin Edwards, Christian Janssen, Sandy Gould, and Benjamin R Cowan. 2021. Eliciting spoken interruptions to inform proactive speech agent design. In Proc. CUI. 1–12.

Digital Library

[11]

Isaac Elias, Heiga Zen, Jonathan Shen, Yu Zhang, Jia Ye, R. J. Skerry-Ryan, and Yonghui Wu. 2021. Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling. CoRR abs/2103.14574 (2021).

[12]

Andrew Gibiansky, Sercan Arik, Gregory Diamos, John Miller, Kainan Peng, Wei Ping, Jonathan Raiman, and Yanqi Zhou. 2017. Deep voice 2: Multi-speaker neural text-to-speech. Adv Neural Inf Process Syst. 30 (2017).

[13]

Ella Glikson and Anita Williams Woolley. 2020. Human trust in artificial intelligence: Review of empirical research. Acad. Manag. Ann. 14, 2 (2020), 627–660.

[14]

Daena J Goldsmith. 2000. Soliciting advice: The role of sequential placement in mitigating face threat. Commun. Monogr. 67, 1 (2000), 1–19.

[15]

Ted Grover, Kael Rowan, Jina Suh, Daniel McDuff, and Mary Czerwinski. 2020. Design and evaluation of intelligent agent prototypes for assistance with focus and productivity at work. In Proc. IUI. 390–400.

Digital Library

[16]

Dietmar Jannach. 2022. Evaluating conversational recommender systems. Artif. Intell. Rev. (2022).

[17]

Matthias Kraus, Nicolas Wagner, and Wolfgang Minker. 2020. Effects of proactive dialogue strategies on human-computer trust. In Proc. UMAP. 107–116.

Digital Library

[18]

Matthias Kraus, Nicolas Wagner, Nico Untereiner, and Wolfgang Minker. 2022. Including Social Expectations for Trustworthy Proactive Human-Robot Dialogue. In Proc. UMAP. 23–33.

Digital Library

[19]

Katharina Kühne, Martin H Fischer, and Yuefang Zhou. 2020. The human takes it all: Humanlike synthesized voices are perceived as less eerie and more likable. evidence from a subjective ratings study. Frontiers in neurorobotics (2020), 105.

[20]

Ewa Luger and Abigail Sellen. 2016. " Like Having a Really Bad PA" The Gulf between User Expectation and Experience of Conversational Agents. In Proc. CHI. 5286–5297.

[21]

Michal Luria, Rebecca Zheng, Bennett Huffman, Shuangni Huang, John Zimmerman, and Jodi Forlizzi. 2020. Social boundaries for personal agents in the interpersonal space of the home. In Proc. CHI. 1–12.

Digital Library

[22]

Erina L MacGeorge, Bo Feng, Ginger L Butler, and Sara K Budarz. 2004. Understanding advice in supportive interactions: Beyond the facework and message evaluation paradigm. Hum. Commun. Res. 30, 1 (2004), 42–70.

[23]

Janne A Martikainen, Erkki JO Soini, David E Laaksonen, and Leo Niskanen. 2011. Health economic consequences of reducing salt intake and replacing saturated fat with polyunsaturated fat in the adult Finnish population: estimates based on the FINRISK and FINDIET studies. Eur J Clin Nutr. 65, 10 (2011), 1148–1155.

[24]

Manolis Mavrikis, Beate Grawemeyer, Alice Hansen, and Sergio Gutierrez-Santos. 2014. Exploring the potential of speech recognition to support problem solving and reflection. In Int. J. Technol. Enhanc. Learn. Springer, 263–276.

[25]

National Public Media. 2022. The Smart Audio Report | National Public Media — nationalpublicmedia.com. https://www.nationalpublicmedia.com/insights/reports/smart-audio-report/. [Accessed 04-Apr-2023].

[26]

John W Mullennix, Steven E Stern, Stephen J Wilson, and Corrie-lynn Dyson. 2003. Social perception of male and female computer synthesized speech. Comput. Hum. Behav. 19, 4 (2003), 407–424.

[27]

Lingyun Qiu and Izak Benbasat. 2009. Evaluating anthropomorphic product recommendation agents: A social relationship perspective to designing information systems. J Manag Inf Syst. 25, 4 (2009), 145–182.

Digital Library

[28]

Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever. 2021. Zero-shot text-to-image generation. In Proc. ICML. PMLR, 8821–8831.

[29]

Leon Reicherts, Yvonne Rogers, Licia Capra, Ethan Wood, Tu Dinh Duong, and Neil Sebire. 2022. It’s Good to Talk: A Comparison of Using Voice Versus Screen-Based Interactions for Agent-Assisted Tasks. ACM Trans. Comput. Hum. Interact. 29, 3 (2022), 1–41.

Digital Library

[30]

Leon Reicherts, Nima Zargham, Michael Bonfert, Yvonne Rogers, and Rainer Malaka. 2021. May I Interrupt? Diverging Opinions on Proactive Smart Speakers. In Proc. CUI. 1–10.

Digital Library

[31]

Julian B Rotter. 1980. Interpersonal trust, trustworthiness, and gullibility.American psychologist 35, 1 (1980), 1.

[32]

Katie Seaborn, Norihisa P Miyake, Peter Pennefather, and Mihoko Otake-Matsuura. 2021. Voice in human–agent interaction: a survey. ACM Comput. Surv. 54, 4 (2021), 1–43.

Digital Library

[33]

Ben Shneiderman. 2020. Human-centered artificial intelligence: Three fresh ideas. AIS Trans. Hum.-Comput. Interact. 12, 3 (2020), 109–124.

[34]

Kathleen S Verderber, Rudolph F Verderber, and Cynthia Berryman-Fink. 2004. Inter-act: Interpersonal communication concepts, skills, and contexts. Oxford University Press New York.

[35]

Sarah Theres Völkel, Daniel Buschek, Malin Eiband, Benjamin R Cowan, and Heinrich Hussmann. 2021. Eliciting and Analysing Users’ Envisioned Dialogues with Perfect Voice Assistants. In Proc. CHI. 1–15.

Digital Library

[36]

Nima Zargham, Leon Reicherts, Michael Bonfert, Sarah Theres Völkel, Johannes Schöning, Rainer Malaka, and Yvonne Rogers. 2022. Understanding Circumstances for Desirable Proactive Behaviour of Voice Assistants: The Proactivity Dilemma. In Proc. CUI.

Digital Library

Cited By

Dubiel MSergeeva ALeiva L(2024)Impact of Voice Fidelity on Decision Making: A Potential Dark Pattern?Proceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645202(181-194)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645202
Smith RDragone M(2024)Exploring the Impact of Confirmation and Interaction During Human-Robot Collaboration with a Proactive Robot Assistant2024 33rd IEEE International Conference on Robot and Human Interactive Communication (ROMAN)10.1109/RO-MAN60168.2024.10731366(2007-2014)Online publication date: 26-Aug-2024
https://doi.org/10.1109/RO-MAN60168.2024.10731366
Zargham NReicherts LAvanesi VRogers YMalaka R(2023)Tickling Proactivity: Exploring the Use of Humor in Proactive Voice AssistantsProceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia10.1145/3626705.3627777(294-320)Online publication date: 3-Dec-2023
https://dl.acm.org/doi/10.1145/3626705.3627777

Index Terms

Are you sure you want to order that?: On Appropriateness of Voice-only Proactive Feedback Strategies
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Natural language interfaces
    2. Interaction techniques
      1. Auditory feedback
  2. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing design and evaluation methods

Recommendations

Conversational Agents Trust Calibration: A User-Centred Perspective to Design
CUI '22: Proceedings of the 4th Conference on Conversational User Interfaces

Previous work identified trust as one of the key requirements for adoption and continued use of conversational agents (CAs). Given recent advances in natural language processing and deep learning, it is currently possible to execute simple goal-oriented ...
“Hey Genie, You Got Me Thinking about My Menu Choices!” Impact of Proactive Feedback on User Perception and Reflection in Decision-making Tasks
Conversational agents (CAs) that deliver proactive interventions can benefit users by reducing their cognitive workload and improving performance. However, little is known regarding how such interventions would impact users’ reflection on choices in voice-...
How to leverage anthropomorphism for chatbot service interfaces: The interplay of communication style and personification
Abstract
Although chatbots are oftentimes used in customer service encounters, interactions are oftentimes perceived as not satisfactory. One key aspect for designing chatbots is the use of anthropomorphic design elements. In this experimental study, we ...
Highlights
- Anthropomorphic design elements significantly influence social presence.
- Social presence influences trusting beliefs, empathy, and satisfaction.
- Social presence is a mediator for anthropomorphic design on chatbot satisfaction.
- ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

CUI '23: Proceedings of the 5th International Conference on Conversational User Interfaces

July 2023

504 pages

ISBN:9798400700149

DOI:10.1145/3571884

Editors:
Minha Lee
Eindhoven University of Technology, Netherlands
,
Cosmin Munteanu
University of Waterloo, Canada
,
Martin Porcheron
Bold Insight, UK
,
Johanne Trippas
RMIT University, Australia
,
Sarah Theres Völkel
Google, Germany

Copyright © 2023 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.

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 July 2023

Check for updates

Author Tags

Qualifiers

Work in progress
Research
Refereed limited

Funding Sources

Horizon 2020 FET program of the European Union
Luxembourg National Research Fund (FNR)
European Innovation Council Pathfinder

Conference

CUI '23

Sponsor:

SIGCHI

CUI '23: ACM conference on Conversational User Interfaces

July 19 - 21, 2023

Eindhoven, Netherlands

Acceptance Rates

Overall Acceptance Rate 34 of 100 submissions, 34%

Upcoming Conference

CUI '25

Sponsor:
sigchi

ACM Conversational User Interfaces 2025

July 7 - 9, 2025

Waterloo , ON , Canada

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
179
Total Downloads

Downloads (Last 12 months)106
Downloads (Last 6 weeks)1

Reflects downloads up to 05 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Dubiel MSergeeva ALeiva L(2024)Impact of Voice Fidelity on Decision Making: A Potential Dark Pattern?Proceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645202(181-194)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645202
Smith RDragone M(2024)Exploring the Impact of Confirmation and Interaction During Human-Robot Collaboration with a Proactive Robot Assistant2024 33rd IEEE International Conference on Robot and Human Interactive Communication (ROMAN)10.1109/RO-MAN60168.2024.10731366(2007-2014)Online publication date: 26-Aug-2024
https://doi.org/10.1109/RO-MAN60168.2024.10731366
Zargham NReicherts LAvanesi VRogers YMalaka R(2023)Tickling Proactivity: Exploring the Use of Humor in Proactive Voice AssistantsProceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia10.1145/3626705.3627777(294-320)Online publication date: 3-Dec-2023
https://dl.acm.org/doi/10.1145/3626705.3627777

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View Table of Contents