Nothing Special   »   [go: up one dir, main page]

skip to main content
research-article

Understanding User Perceptions of Proactive Smart Speakers

Published: 30 December 2021 Publication History

Abstract

Voice assistants, such as Amazon's Alexa and Google Home, increasingly find their way into consumer homes. Their functionality, however, is currently limited to being passive answer machines rather than proactively engaging users in conversations. Speakers' proactivity would open up a range of important application scenarios, including health services, such as checking in on patient states and triggering medication reminders. It remains unclear how passive speakers should implement proactivity. To better understand user perceptions, we ran a 3-week field study with 13 participants where we modified the off-the-shelf Google Home to become proactive. During the study, our speaker proactively triggered conversations that were essentially Experience Sampling probes allowing us to identify when to engage users. Applying machine-learning, we are able to predict user responsiveness with a 71.6% accuracy and find predictive features. We also identify self-reported factors, such as boredom and mood, that are significantly correlated with users' perceived availability. Our prototype and findings inform the design of proactive speakers that verbally engage users at opportune moments and contribute to the design of proactive application scenarios and voice-based experience sampling studies.

References

[1]
Rebecca Adaimi, Howard Yong, and Edison Thomaz. 2021. Ok Google, What Am I Doing? Acoustic Activity Recognition Bounded by Conversational Assistant Interactions. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 5, 1, Article 2 (mar 2021), 24 pages. https://doi.org/10.1145/3448090
[2]
Adrian Bangerter, Eric Chevalley, and Sylvie Derouwaux. 2010. Managing third-party interruptions in conversations: Effects of duration and conversational role. Journal of Language and Social Psychology 29, 2 (feb 2010), 235--244. https://doi.org/10.1177/0261927x09359591
[3]
Erin Beneteau, Ashley Boone, Yuxing Wu, Julie A. Kientz, Jason Yip, and Alexis Hiniker. 2020. Parenting with Alexa: Exploring the Introduction of Smart Speakers on Family Dynamics. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. ACM, 1--13. https://doi.org/10.1145/3313831.3376344
[4]
Erin Beneteau, Olivia K. Richards, Mingrui Zhang, Julie A. Kientz, Jason Yip, and Alexis Hiniker. 2019. Communication breakdowns between families and Alexa. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM, 1--13. https://doi.org/10.1145/3290605.3300473
[5]
Frank Bentley, Chris Luvogt, Max Silverman, Rushani Wirasinghe, Brooke White, and Danielle Lottridge. 2018. Understanding the long-term use of smart speaker assistants. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 3 (sep 2018), 1--24. https://doi.org/10.1145/3264901
[6]
Meera M Blattner, Denise A Sumikawa, and Robert M Greenberg. 1990. Earcons and icons: Their structure and common design principles. Applied Ergonomics 21, 2 (jun 1990), 165--166. https://doi.org/10.1016/0003-6870(90)90160-y
[7]
Matthias Braunhofer, Francesco Ricci, Béatrice Lamche, and Wolfgang Wörndl. 2015. A context-aware model for proactive recommender systems in the tourism domain. In Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct. ACM, 1070--1075. https://doi.org/10.1145/2786567.2794332
[8]
Narae Cha, Auk Kim, Cheul Young Park, Soowon Kang, Mingyu Park, Jae-Gil Lee, Sangsu Lee, and Uichin Lee. 2020. Hello There! Is Now a Good Time to Talk? Opportune Moments for Proactive Interactions with Smart Speakers. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 3 (sep 2020), 1--28. https://doi.org/10.1145/3411810
[9]
Yung-Ju Chang and John C. Tang. 2015. Investigating mobile users' ringer mode usage and attentiveness and responsiveness to communication. In Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services. ACM, 6--15. https://doi.org/10.1145/2785830.2785852
[10]
Tianqi Chen and Carlos Guestrin. 2016. Xgboost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 785--794. https://doi.org/10.1145/2939672.2939785
[11]
Eun Kyoung Choe, Sunny Consolvo, Jaeyeon Jung, Beverly Harrison, and Julie A. Kientz. 2011. Living in a Glass House: A Survey of Private Moments in the Home. In Proceedings of the 13th international conference on Ubiquitous computing - UbiComp '11 (Beijing, China) (UbiComp '11). ACM Press, New York, NY, USA, 41--44. https://doi.org/10.1145/2030112.2030118
[12]
Woohyeok Choi, Sangkeun Park, Duyeon Kim, Youn kyung Lim, and Uichin Lee. 2019. Multi-stage receptivity model for mobile just-in-time health intervention. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 2 (jun 2019), 1--26. https://doi.org/10.1145/3328910
[13]
Julien Cumin, Grregoire Lefebvre, Fano Ramparany, and James L. Crowley. 2018. Inferring availability for communication in smart homes using context. In 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE, IEEE, 1--6. https://doi.org/10.1109/percomw.2018.8480091
[14]
Maria Danninger, Tobias Kluge, and Rainer Stiefelhagen. 2006. MyConnector: analysis of context cues to predict human availability for communication. In Proceedings of the 8th international conference on Multimodal interfaces - ICMI '06. ACM Press, 12--19. https://doi.org/10.1145/1180995.1181001
[15]
Anind K. Dey, Katarzyna Wac, Denzil Ferreira, Kevin Tassini, Jin-Hyuk Hong, and Julian Ramos. 2011. Getting closer: an empirical investigation of the proximity of user to their smart phones. In Proceedings of the 13th international conference on Ubiquitous computing - UbiComp '11. ACM Press, 163--172. https://doi.org/10.1145/2030112.2030135
[16]
Don A. Dillman, Glenn Phelps, Robert Tortora, Karen Swift, Julie Kohrell, Jodi Berck, and Benjamin L. Messer. 2009. Response rate and measurement differences in mixed-mode surveys using mail, telephone, interactive voice response (IVR) and the Internet. Social Science Research 38, 1 (mar 2009), 1--18. https://doi.org/10.1016/j.ssresearch.2008.03.007
[17]
Joel E. Fischer, Chris Greenhalgh, and Steve Benford. 2011. Investigating episodes of mobile phone activity as indicators of opportune moments to deliver notifications. In Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services - MobileHCI '11. ACM Press, 181--190. https://doi.org/10.1145/2037373.2037402
[18]
Robert Fisher and Reid Simmons. 2011. Smartphone interruptibility using density-weighted uncertainty sampling with reinforcement learning. In 2011 10th International Conference on Machine Learning and Applications and Workshops, Vol. 1. IEEE, IEEE, 436--441. https://doi.org/10.1109/icmla.2011.128
[19]
James Fogarty, Scott E. Hudson, and Jennifer Lai. 2004. Examining the robustness of sensor-based statistical models of human interruptibility. In Proceedings of the 2004 conference on Human factors in computing systems - CHI '04. ACM Press, 207--214. https://doi.org/10.1145/985692.985719
[20]
Radhika Garg and Subhasree Sengupta. 2020. He is just like me: a study of the long-term use of smart speakers by parents and children. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 1 (mar 2020), 1--24. https://doi.org/10.1145/3381002
[21]
R. Gockley, A. Bruce, J. Forlizzi, M. Michalowski, A. Mundell, S. Rosenthal, B. Sellner, R. Simmons, K. Snipes, A.C. Schultz, and Jue Wang. 2005. Designing robots for long-term social interaction. In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, IEEE, 1338--1343. https://doi.org/10.1109/iros.2005.1545303
[22]
Danula Hettiachchi, Zhanna Sarsenbayeva, Fraser Allison, Niels van Berkel, Tilman Dingler, Gabriele Marini, Vassilis Kostakos, and Jorge Goncalves. 2020. "Hi! I am the Crowd Tasker" Crowdsourcing through Digital Voice Assistants. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. ACM, 1--14. https://doi.org/10.1145/3313831.3376320
[23]
Joyce Ho and Stephen S. Intille. 2005. Using context-aware computing to reduce the perceived burden of interruptions from mobile devices. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 909--918. https://doi.org/10.1145/1054972.1055100
[24]
Yue Huang, Borke Obada-Obieh, and Konstantin (Kosta) Beznosov. 2020. Amazon vs. my brother: How users of shared smart speakers perceive and cope with privacy risks. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. ACM, 1--13. https://doi.org/10.1145/3313831.3376529
[25]
Scott Hudson, James Fogarty, Christopher Atkeson, Daniel Avrahami, Jodi Forlizzi, Sara Kiesler, Johnny Lee, and Jie Yang. 2003. Predicting human interruptibility with sensors: a wizard of oz feasibility study. In Proceedings of the conference on Human factors in computing systems - CHI '03. ACM Press, 257--264. https://doi.org/10.1145/642611.642657
[26]
Shamsi T. Iqbal and Brian P. Bailey. 2010. Oasis: A framework for linking notification delivery to the perceptual structure of goal-directed tasks. ACM Transactions on Computer-Human Interaction 17, 4 (dec 2010), 1--28. https://doi.org/10.1145/1879831.1879833
[27]
Cory D. Kidd, Robert Orr, Gregory D. Abowd, Christopher G. Atkeson, Irfan A. Essa, Blair MacIntyre, Elizabeth Mynatt, Thad E. Starner, and Wendy Newstetter. 1999. The aware home: A living laboratory for ubiquitous computing research. In Cooperative Buildings. Integrating Information, Organizations, and Architecture. Springer, Springer Berlin Heidelberg, 191--198. https://doi.org/10.1007/10705432_17
[28]
Auk Kim, Woohyeok Choi, Jungmi Park, Kyeyoon Kim, and Uichin Lee. 2018. Interrupting Drivers for Interactions: Predicting Opportune Moments for In-vehicle Proactive Auditory-verbal Tasks. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 4 (dec 2018), 1--28. https://doi.org/10.1145/3287053
[29]
Auk Kim, Jung-Mi Park, and Uichin Lee. 2020. Interruptibility for In-vehicle Multitasking: Influence of Voice Task Demands and Adaptive Behaviors. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 1 (mar 2020), 1--22. https://doi.org/10.1145/3381009
[30]
Soomin Kim, Joonhwan Lee, and Gahgene Gweon. 2019. Comparing data from chatbot and web surveys: Effects of platform and conversational style on survey response quality. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM, 1--12. https://doi.org/10.1145/3290605.3300316
[31]
Ahmet Baki Kocaballi, Shlomo Berkovsky, Juan C Quiroz, Liliana Laranjo, Huong Ly Tong, Dana Rezazadegan, Agustina Briatore, and Enrico Coiera. 2019. The personalization of conversational agents in health care: systematic review. Journal of Medical Internet Research 21, 11 (nov 2019), e15360. https://doi.org/10.2196/15360
[32]
Mitsuki Komori, Yuichiro Fujimoto, Jianfeng Xu, Kazuyuki Tasaka, Hiromasa Yanagihara, and Kinya Fujita. 2019. Experimental Study on Estimation of Opportune Moments for Proactive Voice Information Service Based on Activity Transition for People Living Alone. In Human-Computer Interaction. Perspectives on Design. Springer, Springer International Publishing, 527--539. https://doi.org/10.1007/978-3-030-22646-6_39
[33]
Dimosthenis Kontogiorgos, Andre Pereira, Boran Sahindal, Sanne van Waveren, and Joakim Gustafson. 2020. Behavioural responses to robot conversational failures. In Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction. ACM, 53--62. https://doi.org/10.1145/3319502.3374782
[34]
Kara A. Latorella. 1998. Effects of modality on interrupted flight deck performance: Implications for data link, In Proceedings of the human factors and ergonomics society annual meeting. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42, 1, 87--91. https://doi.org/10.1177/154193129804200120
[35]
Kara A Latorella. 1999. Investigating interruptions: Implications for flightdeck performance. Vol. 99. NASA.
[36]
Josephine Lau, Benjamin Zimmerman, and Florian Schaub. 2018. Alexa, are you listening? privacy perceptions, concerns and privacy-seeking behaviors with smart speakers. Proceedings of the ACM on Human-Computer Interaction 2, CSCW (nov 2018), 1--31. https://doi.org/10.1145/3274371
[37]
Dongkeon Lee, Kyo-Joong Oh, and Ho-Jin Choi. 2017. The chatbot feels you-a counseling service using emotional response generation. In 2017 IEEE International Conference on Big Data and Smart Computing (BigComp). IEEE, IEEE, 437--440. https://doi.org/10.1109/bigcomp.2017.7881752
[38]
Luis Leiva, Matthias Böhmer, Sven Gehring, and Antonio Krüger. 2012. Back to the app: the costs of mobile application interruptions. In Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services - MobileHCI '12. ACM Press, 291--294. https://doi.org/10.1145/2371574.2371617
[39]
Robert LiKamWa, Yunxin Liu, Nicholas D. Lane, and Lin Zhong. 2013. Moodscope: Building a mood sensor from smartphone usage patterns. In Proceeding of the 11th annual international conference on Mobile systems, applications, and services - MobiSys '13. ACM Press, 389--402. https://doi.org/10.1145/2462456.2483967
[40]
Irene Lopatovska and Harriet Williams. 2018. Personification of the Amazon Alexa: BFF or a mindless companion. In Proceedings of the 2018 Conference on Human Information Interaction&Retrieval - CHIIR '18. ACM Press, 265--268. https://doi.org/10.1145/3176349.3176868
[41]
Max M. Louwerse, Arthur C. Graesser, Shulan Lu, and Heather H. Mitchell. 2005. Social cues in animated conversational agents. Applied Cognitive Psychology 19, 6 (2005), 693--704. https://doi.org/10.1002/acp.1117
[42]
Yuhan Luo, Bongshin Lee, and Eun Kyoung Choe. 2020. TandemTrack: Shaping consistent exercise experience by complementing a mobile app with a smart speaker. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1--13.
[43]
Gloria Mark, Shamsi T. Iqbal, Mary Czerwinski, Paul Johns, Akane Sano, and Yuliya Lutchyn. 2016. Email duration, batching and self-interruption: Patterns of email use on productivity and stress. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 1717--1728. https://doi.org/10.1145/2858036.2858262
[44]
Aleksandar Matic, Martin Pielot, and Nuria Oliver. 2015. Boredom-computer interaction: Boredom proneness and the use of smartphone. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp '15. ACM Press, 837--841. https://doi.org/10.1145/2750858.2807530
[45]
Thanassis Mavropoulos, Georgios Meditskos, Spyridon Symeonidis, Eleni Kamateri, Maria Rousi, Dimitris Tzimikas, Lefteris Papageorgiou, Christos Eleftheriadis, George Adamopoulos, Stefanos Vrochidis, and Ioannis Kompatsiaris. 2019. A context-aware conversational agent in the rehabilitation domain. Future Internet 11, 11 (nov 2019), 231. https://doi.org/10.3390/fi11110231
[46]
Alexander Meschtscherjakov, Astrid Weiss, and Thomas Scherndl. 2009. Utilizing emoticons on mobile devices within ESM studies to measure emotions in the field. Proc. MME in conjunction with MobileHCI 9 (2009), 3361--3366.
[47]
Kristine S. Nagel, James M. Hudson, and Gregory D. Abowd. 2004. Predictors of availability in home life context-mediated communication. In Proceedings of the 2004 ACM conference on Computer supported cooperative work - CSCW '04. ACM Press, 497--506. https://doi.org/10.1145/1031607.1031689
[48]
Jon O'Brien, Tom Rodden, Mark Rouncefield, and John Hughes. 1999. At home with the technology: an ethnographic study of a set-top-box trial. ACM Transactions on Computer-Human Interaction 6, 3 (sep 1999), 282--308. https://doi.org/10.1145/329693.329698
[49]
Tadashi Okoshi, Julian Ramos, Hiroki Nozaki, Jin Nakazawa, Anind K. Dey, and Hideyuki Tokuda. 2015. Attelia: Reducing user's cognitive load due to interruptive notifications on smart phones. In 2015 IEEE International Conference on Pervasive Computing and Communications (PerCom). IEEE, IEEE, 96--104. https://doi.org/10.1109/percom.2015.7146515
[50]
Veljko Pejovic and Mirco Musolesi. 2014. InterruptMe: designing intelligent prompting mechanisms for pervasive applications. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 897--908. https://doi.org/10.1145/2632048.2632062
[51]
Veljko Pejovic, Mirco Musolesi, and Abhinav Mehrotra. 2015. Investigating the role of task engagement in mobile interruptibility. In Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct. ACM, 1100--1105. https://doi.org/10.1145/2786567.2794336
[52]
Martin Pielot, Bruno Cardoso, Kleomenis Katevas, Joan Ser à, Aleksandar Matic, and Nuria Oliver. 2017. Beyond interruptibility: Predicting opportune moments to engage mobile phone users. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1, 3 (sep 2017), 1--25. https://doi.org/10.1145/3130956
[53]
Martin Pielot, Karen Church, and Rodrigo de Oliveira. 2014. An in-situ study of mobile phone notifications. In Proceedings of the 16th international conference on Human-computer interaction with mobile devices & services - MobileHCI '14. ACM Press, 233--242. https://doi.org/10.1145/2628363.2628364
[54]
Martin Pielot, Tilman Dingler, Jose San Pedro, and Nuria Oliver. 2015. When attention is not scarce-detecting boredom from mobile phone usage. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp '15. ACM Press, 825--836. https://doi.org/10.1145/2750858.2804252
[55]
Martin Pielot, Rodrigo De Oliveira, Haewoon Kwak, and Nuria Oliver. 2014. Didn't you see my message? predicting attentiveness to mobile instant messages. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 3319--3328.
[56]
John D Piette, Morris Weinberger, Stephen J McPhee, Connie A Mah, Fredric B Kraemer, and Lawrence M Crapo. 2000. Do automated calls with nurse follow-up improve self-care and glycemic control among vulnerable patients with diabetes? The American Journal of Medicine 108, 1 (jan 2000), 20--27. https://doi.org/10.1016/s0002-9343(99)00298-3
[57]
Martin Porcheron, Joel E Fischer, Stuart Reeves, and Sarah Sharples. 2018. Voice interfaces in everyday life. In proceedings of the 2018 CHI conference on human factors in computing systems. 1--12.
[58]
David Priest. 2020. What all those lights on your Amazon Echo mean. https://www.cnet.com/how-to/what-do-the-light-ring-colors-on-your-amazon-echo-mean/
[59]
Aung Pyae and Tapani N. Joelsson. 2018. Investigating the usability and user experiences of voice user interface: a case of Google home smart speaker. In Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct. ACM, 127--131. https://doi.org/10.1145/3236112.3236130
[60]
Antoine Raux, Brian Langner, Dan Bohus, Alan W Black, and Maxine Eskenazi. 2005. Let's Go Public! Taking a spoken dialog system to the real world. In Ninth European conference on speech communication and technology.
[61]
Karen Renaud, Judith Ramsay, and Mario Hair. 2006. "You've got e-mail!"... shall I deal with it now? Electronic mail from the recipient's perspective. International Journal of Human-Computer Interaction 21, 3 (2006), 313--332. https://doi.org/10.1036/1097-8542.225550
[62]
Simon Robinson, Jennifer Pearson, Shashank Ahire, Rini Ahirwar, Bhakti Bhikne, Nimish Maravi, and Matt Jones. 2018. Revisiting "hole in the wall" computing: Private smart speakers and public slum settings. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. 1--11.
[63]
Hillol Sarker, Moushumi Sharmin, Amin Ahsan Ali, Md. Mahbubur Rahman, Rummana Bari, Syed Monowar Hossain, and Santosh Kumar. 2014. Assessing the availability of users to engage in just-in-time intervention in the natural environment. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 909--920. https://doi.org/10.1145/2632048.2636082
[64]
Jeremiah Smith and Naranker Dulay. 2014. Ringlearn: Long-term mitigation of disruptive smartphone interruptions. In 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS). IEEE, IEEE, 27--35. https://doi.org/10.1109/percomw.2014.6815160
[65]
Ulla Sonn, Kristina Törnquist, and Elisabeth Svensson. 1999. The ADL taxonomy-from individual categorical data to ordinal categorical data. Scandinavian Journal of Occupational Therapy 6, 1 (jan 1999), 11--20. https://doi.org/10.1080/110381299443807
[66]
Sabine Sonnentag, Leonard Reinecke, Jutta Mata, and Peter Vorderer. 2017. Feeling interrupted-Being responsive: How online messages relate to affect at work. Journal of Organizational Behavior 39, 3 (oct 2017), 369--383. https://doi.org/10.1002/job.2239
[67]
NA Stanton, RT Booth, and RB Stammers. 1993. Alarms in human supervisory control: A human factors perspective. Applied Ergonomics 24, 4 (aug 1993), 299. https://doi.org/10.1016/0003-6870(93)90495-u
[68]
Roger Tourangeau, Mick P Couper, and Darby M Steiger. 2003. Humanizing self-administered surveys: experiments on social presence in web and IVR surveys. Computers in Human Behavior 19, 1 (jan 2003), 1--24. https://doi.org/10.1016/s0747-5632(02)00032-8
[69]
Christopher D. Wickens. 2008. Multiple resources and mental workload. Human Factors: The Journal of the Human Factors and Ergonomics Society 50, 3 (jun 2008), 449--455. https://doi.org/10.1518/001872008x288394
[70]
Fengpeng Yuan, Xianyi Gao, and Janne Lindqvist. 2017. How busy are you? Predicting the interruptibility intensity of mobile users. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 5346--5360. https://doi.org/10.1145/3025453.3025946
[71]
Chenyang Zhang and Yingli Tian. 2012. RGB-D camera-based daily living activity recognition. Journal of computer vision and image processing 2, 4 (2012), 12.
[72]
Manuela Züger and Thomas Fritz. 2015. Interruptibility of software developers and its prediction using psycho-physiological sensors. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, 2981--2990. https://doi.org/10.1145/2702123.2702593

Cited By

View all
  • (2024)Investigating the Integration and the Long-Term Use of Smart Speakers in Older Adults’ Daily Practices: Qualitative StudyJMIR mHealth and uHealth10.2196/4747212(e47472)Online publication date: 12-Feb-2024
  • (2024)The CoExplorer Technology Probe: A Generative AI-Powered Adaptive Interface to Support Intentionality in Planning and Running Video MeetingsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661507(1638-1657)Online publication date: 1-Jul-2024
  • (2024)Dual-Mode Interventions: Giving Agency to Knowledge Workers in Proactive Health InterventionsProceedings of the 6th ACM Conference on Conversational User Interfaces10.1145/3640794.3665578(1-7)Online publication date: 8-Jul-2024
  • Show More Cited By

Index Terms

  1. Understanding User Perceptions of Proactive Smart Speakers

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
    Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies  Volume 5, Issue 4
    Dec 2021
    1307 pages
    EISSN:2474-9567
    DOI:10.1145/3508492
    Issue’s Table of Contents
    Permission to make digital or hard copies of all or part 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 components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 30 December 2021
    Published in IMWUT Volume 5, Issue 4

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Conversational Agents
    2. Experience Sampling Method
    3. Interruptibility
    4. Smart Speakers

    Qualifiers

    • Research-article
    • Research
    • Refereed

    Funding Sources

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)218
    • Downloads (Last 6 weeks)32
    Reflects downloads up to 12 Nov 2024

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Investigating the Integration and the Long-Term Use of Smart Speakers in Older Adults’ Daily Practices: Qualitative StudyJMIR mHealth and uHealth10.2196/4747212(e47472)Online publication date: 12-Feb-2024
    • (2024)The CoExplorer Technology Probe: A Generative AI-Powered Adaptive Interface to Support Intentionality in Planning and Running Video MeetingsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661507(1638-1657)Online publication date: 1-Jul-2024
    • (2024)Dual-Mode Interventions: Giving Agency to Knowledge Workers in Proactive Health InterventionsProceedings of the 6th ACM Conference on Conversational User Interfaces10.1145/3640794.3665578(1-7)Online publication date: 8-Jul-2024
    • (2024)WorkFit: Designing Proactive Voice Assistance for the Health and Well-Being of Knowledge WorkersProceedings of the 6th ACM Conference on Conversational User Interfaces10.1145/3640794.3665561(1-14)Online publication date: 8-Jul-2024
    • (2024)Towards Detecting and Mitigating Cognitive Bias in Spoken Conversational SearchAdjunct Proceedings of the 26th International Conference on Mobile Human-Computer Interaction10.1145/3640471.3680245(1-10)Online publication date: 21-Sep-2024
    • (2024)Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported DataProceedings of the ACM on Human-Computer Interaction10.1145/36373648:CSCW1(1-35)Online publication date: 26-Apr-2024
    • (2024)CoExplorer: Generative AI Powered 2D and 3D Adaptive Interfaces to Support Intentionality in Video MeetingsExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3650797(1-10)Online publication date: 11-May-2024
    • (2024)Exploring Context-Aware Mental Health Self-Tracking Using Multimodal Smart Speakers in Home EnvironmentsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642846(1-18)Online publication date: 11-May-2024
    • (2024)Interrupting for Microlearning: Understanding Perceptions and Interruptibility of Proactive Conversational Microlearning ServicesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642778(1-21)Online publication date: 11-May-2024
    • (2024)Better to Ask Than Assume: Proactive Voice Assistants’ Communication Strategies That Respect User Agency in a Smart Home EnvironmentProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642193(1-17)Online publication date: 11-May-2024
    • Show More Cited By

    View Options

    Get Access

    Login options

    Full Access

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media