Let Me Ask You This: How Can a Voice Assistant Elicit Explicit User Feedback?
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Ziang Xiao | Jennifer Thom-Santelli | Sarah Mennicken | Bernd Huber | Adam Shonkoff | Jennifer Thom-Santelli | Sarah Mennicken | Bernd Huber | Ziang Xiao | Adam Shonkoff
[1] Jichen Zhu,et al. The Impact of User Characteristics and Preferences on Performance with an Unfamiliar Voice User Interface , 2019, CHI.
[2] S. Porter,et al. Overcoming survey research problems , 2004 .
[3] Loren G. Terveen,et al. Understanding How People Use Natural Language to Ask for Recommendations , 2017, RecSys.
[4] V. Venkatesh,et al. AGE DIFFERENCES IN TECHNOLOGY ADOPTION DECISIONS: IMPLICATIONS FOR A CHANGING WORK FORCE , 2000 .
[5] F. Maxwell Harper,et al. An Economic Model of User Rating in an Online Recommender System , 2005, User Modeling.
[6] Shwetak N. Patel,et al. SwitchBack: Using Focus and Saccade Tracking to Guide Users' Attention for Mobile Task Resumption , 2015, CHI.
[7] Andrea Lockerd Thomaz,et al. Policy Shaping: Integrating Human Feedback with Reinforcement Learning , 2013, NIPS.
[8] Thorsten Joachims,et al. Accurately interpreting clickthrough data as implicit feedback , 2005, SIGIR '05.
[9] Nuria Oliver,et al. I Like It... I Like It Not: Evaluating User Ratings Noise in Recommender Systems , 2009, UMAP.
[10] John Zimmerman,et al. Rapidly Exploring Application Design Through Speed Dating , 2007, UbiComp.
[11] John Riedl,et al. GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.
[12] David R. Large,et al. "It's small talk, jim, but not as we know it.": engendering trust through human-agent conversation in an autonomous, self-driving car , 2019, CUI.
[13] S. Shyam Sundar,et al. Will Deleting History Make Alexa More Trustworthy?: Effects of Privacy and Content Customization on User Experience of Smart Speakers , 2020, CHI.
[14] Cecilia Mascolo,et al. Mobile-Based Experience Sampling for Behaviour Research , 2015, Emotions and Personality in Personalized Services.
[15] Frank Bentley,et al. Understanding the Long-Term Use of Smart Speaker Assistants , 2018, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..
[16] Roger K. Moore. Is Spoken Language All-or-Nothing? Implications for Future Speech-Based Human-Machine Interaction , 2016, IWSDS.
[17] Wei Wang,et al. Recommender system application developments: A survey , 2015, Decis. Support Syst..
[18] Catholijn M. Jonker,et al. Designing interfaces for explicit preference elicitation: a user-centered investigation of preference representation and elicitation process , 2011, User Modeling and User-Adapted Interaction.
[19] F. Conrad,et al. Interactive Feedback Can Improve the Quality of Responses in Web Surveys , 2005 .
[20] Gregory D. Abowd,et al. Towards a Better Understanding of Context and Context-Awareness , 1999, HUC.
[21] Tomás Horváth,et al. Opinion-Driven Matrix Factorization for Rating Prediction , 2013, UMAP.
[22] Chris Van Pelt,et al. Designing a scalable crowdsourcing platform , 2012, SIGMOD Conference.
[23] Bernd Ludwig,et al. InCarMusic: Context-Aware Music Recommendations in a Car , 2011, EC-Web.
[24] Gregory D. Abowd,et al. Farther Than You May Think: An Empirical Investigation of the Proximity of Users to Their Mobile Phones , 2006, UbiComp.
[25] Gediminas Adomavicius,et al. Context-aware recommender systems , 2008, RecSys '08.
[26] Frank Bentley,et al. Music, Search, and IoT , 2019, ACM Trans. Comput. Hum. Interact..
[27] M. Taylor,et al. Consequences of individual feedback on behavior in organizations. , 1979 .
[28] Kim-Phuong L. Vu,et al. Privacy Concerns for Use of Voice Activated Personal Assistant in the Public Space , 2015, Int. J. Hum. Comput. Interact..
[29] John T. Stasko,et al. Be Quiet? Evaluating Proactive and Reactive User Interface Assistants , 2003, INTERACT.
[30] Cecilia Mascolo,et al. EmotionSense: a mobile phones based adaptive platform for experimental social psychology research , 2010, UbiComp.
[31] Chinmay Kulkarni,et al. One Voice Fits All? Social Implications and Research Challenges of Designing Voices for Smart Devices , 2019 .
[32] Scott C. Roesch,et al. Testing the latent factor structure and construct validity of the Ten-Item Personality Inventory , 2009 .
[33] Daniela Braga,et al. Evaluating Voice Quality and Speech Synthesis Using Crowdsourcing , 2013, TSD.
[34] Walid Maalej,et al. When users become collaborators: towards continuous and context-aware user input , 2009, OOPSLA Companion.
[35] Jennifer Thom-Santelli,et al. Giving Voice to Silent Data: Designing with Personal Music Listening History , 2020, CHI.
[36] Judith Masthoff,et al. Designing and Evaluating Explanations for Recommender Systems , 2011, Recommender Systems Handbook.
[37] Florian Alt,et al. At Your Service: Designing Voice Assistant Personalities to Improve Automotive User Interfaces , 2019, CHI.
[38] Gloria Mark,et al. Tell Me About Yourself , 2019, ACM Trans. Comput. Hum. Interact..
[39] Benjamin M. Marlin,et al. Modeling User Rating Profiles For Collaborative Filtering , 2003, NIPS.
[40] Dick de Waard,et al. A simple procedure for the assessment of acceptance of advanced transport telematics , 1997 .
[41] Bruce A. MacDonald,et al. Age and gender factors in user acceptance of healthcare robots , 2009, RO-MAN 2009 - The 18th IEEE International Symposium on Robot and Human Interactive Communication.
[42] Martin Szomszor,et al. Comparison of implicit and explicit feedback from an online music recommendation service , 2010, HetRec '10.
[43] Yehuda Koren,et al. Collaborative filtering with temporal dynamics , 2009, KDD.
[44] LeeUichin,et al. Interruptibility for In-vehicle Multitasking , 2020 .
[45] C. Gallagher. Extending the Linear Model With R: Generalized Linear, Mixed Effects and Nonparametric Regression Models , 2007 .
[46] Matthias Peissner,et al. Voice User Interface Design , 2004, UP.
[47] B. J. Fogg,et al. Can computers be teammates? , 1996, Int. J. Hum. Comput. Stud..
[48] Predrag V. Klasnja,et al. Exploring Privacy Concerns about Personal Sensing , 2009, Pervasive.
[49] Sonia Chiasson,et al. Understanding Fitness Tracker Users' Security and Privacy Knowledge, Attitudes and Behaviours , 2020, CHI.
[50] Anja Bachmann,et al. ESMAC: A Web-Based Configurator for Context-Aware Experience Sampling Apps in Ambulatory Assessment , 2015, EAI Endorsed Trans. Ambient Syst..
[51] Shwetak N. Patel,et al. FarmChat , 2018, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..
[52] Sarah Sharples,et al. Voice Interfaces in Everyday Life , 2018, CHI.
[53] C. Judd,et al. What the Voice Reveals: Within- and Between-Category Stereotyping on the Basis of Voice , 2006, Personality & social psychology bulletin.
[54] Li Chen,et al. A user-centric evaluation framework for recommender systems , 2011, RecSys '11.
[55] Chinmay Kulkarni,et al. Vitro: Designing a Voice Assistant for the Scientific Lab Workplace , 2019, Conference on Designing Interactive Systems.
[56] James A. Landay,et al. MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones , 2007, MobiSys '07.
[57] Eugene Cho,et al. Hey Google, Can I Ask You Something in Private? , 2019, CHI.
[58] E. Diener,et al. Experience Sampling: Promises and Pitfalls, Strengths and Weaknesses , 2003 .
[59] Clifford Nass,et al. Computers are social actors , 1994, CHI '94.
[60] Benjamin R. Cowan,et al. "What can i help you with?": infrequent users' experiences of intelligent personal assistants , 2017, MobileHCI.
[61] Gloria Mark,et al. Tell Me About Yourself , 2019, ACM Trans. Comput. Hum. Interact..
[62] Stephen R. Porter,et al. Multiple Surveys of Students and Survey Fatigue. , 2004 .
[63] Peter Brusilovsky,et al. Explaining recommendations in an interactive hybrid social recommender , 2019, IUI.
[64] Michelle X. Zhou,et al. Who should be my teammates: using a conversational agent to understand individuals and help teaming , 2019, IUI.
[65] Jaime Teevan,et al. Explicit In Situ User Feedback for Web Search Results , 2016, SIGIR.
[66] Gita Taasoobshirazi,et al. Promoting attitude change and expressed willingness to take action toward climate change in college students , 2012 .
[67] Michael S. Bernstein,et al. Conceptual Metaphors Impact Perceptions of Human-AI Collaboration , 2020, Proc. ACM Hum. Comput. Interact..
[68] Lei Zheng,et al. Joint Deep Modeling of Users and Items Using Reviews for Recommendation , 2017, WSDM.
[69] Matthias Söllner,et al. AI-Based Digital Assistants , 2019, Business & Information Systems Engineering.
[70] Robert A. Virzi,et al. Refining the Test Phase of Usability Evaluation: How Many Subjects Is Enough? , 1992 .
[71] Riender Happee,et al. Using Crowdflower to Study the Relationship between Self-Reported Violations and Traffic Accidents , 2015 .
[72] Donghua Tao,et al. Intention to Use and Actual Use of Electronic Information Resources: Further Exploring Technology Acceptance Model (TAM) , 2009, AMIA.
[73] Nadir Weibel,et al. Computational Ethnography: Automated and Unobtrusive Means for Collecting Data In Situ for Human–Computer Interaction Evaluation Studies , 2015 .
[74] Jose M. Such,et al. More than Smart Speakers: Security and Privacy Perceptions of Smart Home Personal Assistants , 2019, SOUPS @ USENIX Security Symposium.
[75] Jose M. Such,et al. Privacy Norms for Smart Home Personal Assistants , 2021, CHI.
[76] E. Weigand. The Routledge Handbook of Language and Dialogue , 2017 .
[77] Biplav Srivastava,et al. Towards an Optimal Dialog Strategy for Information Retrieval Using Both Open- and Close-ended Questions , 2018, IUI.
[78] Louis-Philippe Morency,et al. It's only a computer: Virtual humans increase willingness to disclose , 2014, Comput. Hum. Behav..
[79] M. Alexiades. Ethnobotany in the Third Millennium: expectations and unresolved issues , 2003 .
[80] Hongxin Hu,et al. Measuring the Effectiveness of Privacy Policies for Voice Assistant Applications , 2020, ACSAC.
[81] Traum. David,et al. Computational Approaches to Dialogue , 2017 .
[82] E. Altenmüller,et al. Does music listening in a social context alter experience? A physiological and psychological perspective on emotion , 2011 .
[83] David M. Nichols,et al. Implicit Rating and Filtering , 1998 .
[84] Jennifer Thom-Santelli,et al. Play Music: User Motivations and Expectations for Non-Specific Voice Queries , 2020, ISMIR.
[85] Derry O'Sullivan,et al. Explicit vs Implicit Profiling - A Case-Study in Electronic Programme Guides , 2003, IJCAI.
[86] Chris Speed,et al. The Ethnobot: Gathering Ethnographies in the Age of IoT , 2018, CHI.
[87] Auk Kim,et al. Interruptibility for In-vehicle Multitasking , 2020, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..
[88] Catholijn M. Jonker,et al. Factors Influencing User Motivation for Giving Online Preference Feedback , 2010 .
[89] Roger K. Moore. Appropriate Voices for Artefacts: Some Key Insights , 2017 .
[90] Abigail Sellen,et al. "Like Having a Really Bad PA": The Gulf between User Expectation and Experience of Conversational Agents , 2016, CHI.
[91] Venkatesh,et al. A Longitudinal Field Investigation of Gender Differences in Individual Technology Adoption Decision-Making Processes. , 2000, Organizational behavior and human decision processes.
[92] Markus Zanker,et al. Collaborative Feature-Combination Recommender Exploiting Explicit and Implicit User Feedback , 2009, 2009 IEEE Conference on Commerce and Enterprise Computing.
[93] Ass,et al. Can computers be teammates? , 1996 .
[94] WangWei,et al. Recommender system application developments , 2015 .