Now showing items 1-10 of 23
Predicting Success in Dialogue
Task-solving in dialogue depends on the linguistic alignment of the interlocutors, which Pickering & Garrod (2004) have suggested to be based on mechanistic repetition effects. In this paper, we seek confirmation of ...
Dealing with Interpretation Errors in Tutorial Dialogue.
We describe an approach to dealing with interpretation errors in a tutorial dialogue system. Allowing students to provide explanations and generate contentful talk can be helpful for learning, but the language that ...
Automatic Decision Detection in Meeting Speech
Decision making is an important aspect of meetings in organisational settings, and archives of meeting recordings constitute a valuable source of information about the decisions made. However, standard utilities such as ...
Context and Usability Testing: User-Modeled Information Presentation in Easy and Difficult Driving Conditions
A 2x2 enhanced Wizard-of-Oz experiment (N = 32) was conducted to compare two different approaches to presenting information to drivers in easy and difficult driving conditions. Data of driving safety, evaluation of ...
Understanding student input for tutorial dialogue in procedural domains
We present an analysis of student language input in a corpus of tutoring dialogue in the domain of symbolic differentiation. Our focus on procedural tutoring makes the dialogue comparable to collaborative problem-solving ...
Event extraction in a Plot Advice Agent
In this paper we present how the automatic extraction of events from text can be used to both classify narrative texts according to plot quality and produce advice in an interactive learning environment intended to ...
Being Old Doesn't Mean Acting Old: How Older Users Interact with Spoken Dialogue System.
Most studies on adapting voice interfaces to older users work top-down by comparing the interaction behavior of older and younger users. In contrast, we present a bottom-up approach. A statistical cluster analysis of 447 ...
Report on the First NLG Challenge on Generating Instructions in Virtual Environments (GIVE)
We describe the first installment of the Challenge on Generating Instructions in Virtual Environments (GIVE), a new shared task for the NLG community. We motivate the design of the challenge, describe how we carried it ...
The software architecture for the First Challenge on Generating Instructions in Virtual Environments.
The GIVE Challenge is a new Internet-based evaluation effort for natural language generation systems. In this paper, we motivate and describe the software infrastructure that we developed to support this challenge.