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Current asynchronous voice messaging interfaces, like voicemail, fail to take advantage of our conversational skills. TalkBack restores conversational turn-taking to voicemail retrieval by dividing voice messages into smaller sections based on the most significant silent and filled pauses and pausing after each to record a response. The responses are composed into a reply, alternating with snippets of the original message for context. TalkBack is built into a digital picture frame; the recipient touches a picture of the caller to hear each segment of the message in turn. The minimal interface models synchronous interaction and facilitates asynchronous voice messaging. TalkBack can also present a voice-annotated slide show which it receives over the Internet.

Cameras are a useful source of input for many interactive applications, but computer vision programming is difficult and requires specialized knowledge that is out of reach for many HCI practitioners. In an effort to learn what makes a useful computer vision design tool, we created Eyepatch, a tool for designing camera-based interactions, and evaluated the Eyepatch prototype through deployment to students in an HCI course. This paper describes the lessons we learned about making computer vision more accessible, while retaining enough power and flexibility to be useful in a wide variety of interaction scenarios.

In this paper, we present a methodology for recognizing seatedpostures using data from pressure sensors installed on a chair.Information about seated postures could be used to help avoidadverse effects of sitting for long periods of time or to predictseated activities for a human-computer interface. Our system designdisplays accurate near-real-time classification performance on datafrom subjects on which the posture recognition system was nottrained by using a set of carefully designed, subject-invariantsignal features. By using a near-optimal sensor placement strategy,we keep the number of required sensors low thereby reducing costand computational complexity. We evaluated the performance of ourtechnology using a series of empirical methods including (1)cross-validation (classification accuracy of 87% for ten posturesusing data from 31 sensors), and (2) a physical deployment of oursystem (78% classification accuracy using data from 19sensors).

The human visual system makes a great deal more of images than the elemental marks on a surface. In the course of viewing, creating, or editing a picture, we actively construct a host of visual structures and relationships as components of sensible interpretations. This paper shows how some of these computational processes can be incorporated into perceptually-supported image editing tools, enabling machines to better engage users at the level of their own percepts. We focus on the domain of freehand sketch editors, such as an electronic whiteboard application for a pen-based computer. By using computer vision techniques to perform covert recognition of visual structure as it emerges during the course of a drawing/editing session, a perceptually supported image editor gives users access to visual objects as they are perceived by the human visual system. We present a flexible image interpretation architecture based on token grouping in a multiscale blackboard data structure. This organization supports multiple perceptual interpretations of line drawing data, domain-specific knowledge bases for interpretable visual structures, and gesture-based selection of visual objects. A system implementing these ideas, called PerSketch, begins to explore a new space of WYPIWYG (What You Perceive Is What You Get) image editing tools.

This article describes SwingStates, a library that adds state machines to the Java Swing user interface toolkit. Unlike traditional approaches, which use callbacks or listeners to define interaction, state machines provide a powerful control structure and localize all of the interaction code in one place. SwingStates takes advantage of Java's inner classes, providing programmers with a natural syntax and making it easier to follow and debug the resulting code. SwingStates tightly integrates state machines, the Java language and the Swing toolkit. It reduces the potential for an explosion of states by allowing multiple state machines to work together. We show how to use SwingStates to add new interaction techniques to existing Swing widgets, to program a powerful new Canvas widget and to control high-level dialogues.