Danny Wyatt
University of Washington
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Publication
Featured researches published by Danny Wyatt.
IEEE Pervasive Computing | 2008
Tanzeem Choudhury; Sunny Consolvo; Beverly L. Harrison; Jeffrey Hightower; Anthony LaMarca; Louis LeGrand; Ali Rahimi; Adam D. Rea; G. Bordello; Bruce Hemingway; Predrag Klasnja; Karl Koscher; James A. Landay; Jonathan Lester; Danny Wyatt; Dirk Haehnel
Activity-aware systems have inspired novel user interfaces and new applications in smart environments, surveillance, emergency response, and military missions. Systems that recognize human activities from body-worn sensors can further open the door to a world of healthcare applications, such as fitness monitoring, eldercare support, long-term preventive and chronic care, and cognitive assistance. Wearable systems have the advantage of being with the user continuously. So, for example, a fitness application could use real-time activity information to encourage users to perform opportunistic activities. Furthermore, the general public is more likely to accept such activity recognition systems because they are usually easy to turn off or remove.
ACM Transactions on Intelligent Systems and Technology | 2011
Danny Wyatt; Tanzeem Choudhury; Jeff A. Bilmes; James A. Kitts
New technologies have made it possible to collect information about social networks as they are acted and observed in the wild, instead of as they are reported in retrospective surveys. These technologies offer opportunities to address many new research questions: How can meaningful information about social interaction be extracted from automatically recorded raw data on human behavior? What can we learn about social networks from such fine-grained behavioral data? And how can all of this be done while protecting privacy? With the goal of addressing these questions, this article presents new methods for inferring colocation and conversation networks from privacy-sensitive audio. These methods are applied in a study of face-to-face interactions among 24 students in a graduate school cohort during an academic year. The resulting analysis shows that networks derived from colocation and conversation inferences are quite different. This distinction can inform future research in computational social science, especially work that only measures colocation or employs colocation data as a proxy for conversation networks.
international conference on acoustics, speech, and signal processing | 2007
Danny Wyatt; Tanzeem Choudhury; Henry A. Kautz
The UW dynamic social network study is an effort to automatically observe and model the creation and evolution of a social network formed through spontaneous face-to-face conversations. We have collected more than 4,400 hours of data that capture the real world interactions between 24 subjects over a period of 9 months. The data was recorded in completely unconstrained and natural conditions, but was collected in a manner that protects the privacy of both study participants and non-participants. Despite the privacy constraints, the data allows for many different types of inference that are in turn useful for studying the prosodic and paralinguistic features of truly spontaneous speech across many subjects and over an extended period of time. This paper describes the new challenges and opportunities presented in such a study, our data collection effort, the problems we encountered, and the resulting corpus.
ubiquitous computing | 2008
Danny Wyatt; Jeff A. Bilmes; Tanzeem Choudhury; James A. Kitts
We present an automated approach for studying fine-grained details of social interaction and relationships. Specifically, we analyze the conversational characteristics of a group of 24 individuals over a six-month period, explore the relationship between conversational dynamics and network position, and identify behavioral correlates of tie strengths within a network. The ability to study conversational dynamics and social networks over long time scales, and to investigate their interplay with rigor, objectivity, and transparency will complement the traditional methods for scientific inquiry into social dynamics. They may also enable socially aware ubiquitous computing systems that are cognizant of and responsive to the users engagement with her social environment.
national conference on artificial intelligence | 2005
Danny Wyatt; Matthai Philipose; Tanzeem Choudhury
IEEE Data(base) Engineering Bulletin | 2006
Tanzeem Choudhury; Matthai Philipose; Danny Wyatt; Jonathan Lester
conference of the international speech communication association | 2007
Danny Wyatt; Tanzeem Choudhury; Jeff A. Bilmes
international joint conference on artificial intelligence | 2007
Danny Wyatt; Tanzeem Choudhury; Jeff A. Bilmes; Henry A. Kautz
national conference on artificial intelligence | 2010
Danny Wyatt; Tanzeem Choudhury; Jeff A. Bilmes
national conference on artificial intelligence | 2008
Danny Wyatt; Tanzeem Choudhury; Jeff A. Bilmes