Specification Techniques for Multi-Modal Dialogues in the U-Wish Project

In this paper we describe the development of a specification\ud technique for specifying interactive web-based services. We\ud wanted to design a language that can be a means of\ud communication between designers and developers of interactive services, that makes it easier to develop web-based services fitted to the users and that shortens the pathway from design to implementation. The language, still under development, is based on process algebra and can be\ud connected to the results of task analysis. We have been\ud working on the automatic generation of executable prototypes\ud out of the specifications. In this way the specification\ud language can establish a connection between users, design\ud and implementation. A first version of this language is\ud available as well as prototype tools for executing the specifications. Ideas will be given as to how to make the connection between specifications and task analysis

Textual Economy through Close Coupling of Syntax and Semantics

We focus on the production of efficient descriptions of objects, actions and events. We define a type of efficiency, textual economy, that exploits the hearer's recognition of inferential links to material elsewhere within a sentence. Textual economy leads to efficient descriptions because the material that supports such inferences has been included to satisfy independent communicative goals, and is therefore overloaded in Pollack's sense. We argue that achieving textual economy imposes strong requirements on the representation and reasoning used in generating sentences. The representation must support the generator's simultaneous consideration of syntax and semantics. Reasoning must enable the generator to assess quickly and reliably at any stage how the hearer will interpret the current sentence, with its (incomplete) syntax and semantics. We show that these representational and reasoning requirements are met in the SPUD system for sentence planning and realization.Comment: 10 pages, uses QobiTree.te

Summarisation and visualisation of e-Health data repositories

At the centre of the Clinical e-Science Framework (CLEF) project is a repository of well organised, detailed clinical histories, encoded as data that will be available for use in clinical care and in-silico medical experiments. We describe a system that we have developed as part of the CLEF project, to perform the task of generating a diverse range of textual and graphical summaries of a patient’s clinical history from a data-encoded model, a chronicle, representing the record of the patient’s medical history. Although the focus of our current work is on cancer patients, the approach we describe is generalisable to a wide range of medical areas

Generating a 3D Simulation of a Car Accident from a Formal Description: the CarSim System

The problem of generating a 3D simulation of a car accident from a written description can be divided into two subtasks: the linguistic analysis and the virtual scene generation. As a means of communication between these two system parts, we designed a template formalism to represent a written accident report. The CarSim system processes template formal descriptions and creates corresponding 3D simulations. A planning component models the trajectories and temporal values of every vehicle that is involved in the accident

VirtualHome: Simulating Household Activities via Programs

In this paper, we are interested in modeling complex activities that occur in a typical household. We propose to use programs, i.e., sequences of atomic actions and interactions, as a high level representation of complex tasks. Programs are interesting because they provide a non-ambiguous representation of a task, and allow agents to execute them. However, nowadays, there is no database providing this type of information. Towards this goal, we first crowd-source programs for a variety of activities that happen in people's homes, via a game-like interface used for teaching kids how to code. Using the collected dataset, we show how we can learn to extract programs directly from natural language descriptions or from videos. We then implement the most common atomic (inter)actions in the Unity3D game engine, and use our programs to "drive" an artificial agent to execute tasks in a simulated household environment. Our VirtualHome simulator allows us to create a large activity video dataset with rich ground-truth, enabling training and testing of video understanding models. We further showcase examples of our agent performing tasks in our VirtualHome based on language descriptions.Comment: CVPR 2018 (Oral