model

In this paper, we describe a multimodal interface prototype system based on Dynamical Dialogue Model. This system not only integrates information of speech and gestures, but also controls the response timing in order to realize a smooth interaction between user and computer. Our approach consists of human-human dialogue analysis, and computational modeling of dialogue.

We propose an interaction technique for editing splines that is aimed at professional graphic designers. These users do not take full advantage of existing spline editing software because their mental representations of drawings do not match the underlying conceptual model of the software. Although editing splines by specifying control points and tangents may be appropriate for engineers, graphic designers think more in terms of strokes, shapes, and gestures appropriate for editing drawings. Our interaction technique matches the latter model: curves can be edited by means of marks, similar to the way strokes are naturally overloaded when drawing on paper. We describe this interaction technique and the algorithms used for its implementation.

Most document or information management systems rely on hierarchies to organise documents (e.g. files, email messages or web bookmarks). However, the rigid structures of hierarchical schemes do not mesh well with the more fluid nature of everyday document practices. This paper describes Presto, a prototype system that allows users to organise their documents entirely in terms of the properties those documents hold for users. Properties provide a uniform mechanism for managing, coding, searching, retrieving and interacting with documents. We concentrate in particular on the challenges that property-based approaches present and the architecture we have developed to tackle them.

The home deployment of sensor-based systems offers many opportunities, particularly in the area of using sensor-based systems to support aging in place by monitoring an elder's activities of daily living. But existing approaches to home activity recognition are typically expensive, difficult to install, or intrude into the living space. This paper considers the feasibility of a new approach that "reaches into the home" via the existing infrastructure. Specifically, we deploy a small number of low-cost sensors at critical locations in a home's water distribution infrastructure. Based on water usage patterns, we can then infer activities in the home. To examine the feasibility of this approach, we deployed real sensors into a real home for six weeks. Among other findings, we show that a model built on microphone-based sensors that are placed away from systematic noise sources can identify 100% of clothes washer usage, 95% of dishwasher usage, 94% of showers, 88% of toilet flushes, 73% of bathroom sink activity lasting ten seconds or longer, and 81% of kitchen sink activity lasting ten seconds or longer. While there are clear limits to what activities can be detected when analyzing water usage, our new approach represents a sweet spot in the tradeoff between what information is collected at what cost.