Paper Reading #5: A Framework for Robust and Flexible Handling of Inputs with Uncertainty

Reference Information

A Framework for Robust and Flexible Handling of Inputs with Uncertainty

Julia Schwarz, Scott E. Hudson, Jennifer Mankoff, Andrew D. Wilson

Presented at UIST'10, October 3-6, 2010, New York, New York, USA

Author Bios

• Julia Schwarz is a PhD student at Carnegie Mellon's Human Computer Interaction lab and has interests in natural interaction and handling ambiguous input.
• Scott E. Hudson is a Professor in Carnegie Mellon's Human-Computer Interaction Institute.
• Jennifer Mankoff is an Associate Professor in Carnegie Mellon's Human Computer Interaction lab and holds a PhD from the Georgia Institute of Technology.
• Andrew D. Wilson is a senior researcher at Microsoft Research with a PhD from MIT's Media Lab. He focuses on applying sensing techniques to enable new styles of HCI.

Summary

Hypothesis

Presenting a new framework for handling input with uncertainty.

Methods

Six demonstrations which include tiny buttons that are manipulable using touch input, a text box that can handle multiple interpretations of spoken input, a scrollbar that can respond to inexactly placed input, and buttons which are easier to click for people with motor impairments are used to provide feedback about uncertain inputs.

The paper explains the various stages in processing of an uncertain inputs and then later shows how to encompass the framework they designed into those stages, like which interactor should receive an event. They then run the system thorough an example where a button is presses ambiguously. The framework is primarily based on probability and PMF calculations.They perform tests on 6 different cases of ambiguous inputs and describe how each of the cases are handled by the framework.

Results

The first set of demonstrations shows that it was easy to adapt to the flexibility of the interface.  There is ambiguity in determining what the user intends to interact with, but the system helps handle the process of deciding.  The authors say that their framework has the potential to enable entirely new forms of interaction, which can adjust their responses based on how likely they are to be pressed.  The second set of demonstrations showed that the framework was very capable of handling multiple interpretations of alternative events with little to no extra development.  Finally, the last demonstration proved that the framework was capable of handling the input robustly, missing only two cases out of over 400.

Contents

New means of interaction mean that the certainty of inputs is no longer assumable. Conventional input frameworks may resolve uncertainty in an undesirable way. The presented framework can temporarily keep track of possibilities for uncertain input to allow for a more informed decision. Conventional frameworks model inputs, dispatch to an object, interpret what events occurred, and take an action. The interpretations of the proposed framework use a probability mass function to guess what the event was meant to do. Integration with conventional interactors is not yet implemented. A wrapper would be used for this.

Discussion

Although there was a demo on their method I wish there was more feedback from actual users or more intense method of participation by people in regards to the products effectiveness. I really had a sense of connection with this paper because I have to deal with input problems all the time. This is sometimes cause I’m not paying attention or cause the devices themselves are not so friendly.