In this paper, we describe RavenClaw, a plan-based, task-independent dialog management
framework. RavenClaw isolates the domain-specific aspects of the dialog control logic from …

In this paper, we present IrisTK-a toolkit for rapid development of real-time systems for multi-
party face-to-face interaction. The toolkit consists of a message passing system, a set of …

This paper describes a fully incremental dialogue system that can engage in dialogues in a
simple domain, number dictation. Because it uses incremental speech recognition and …

Event detection (ED) is a pivotal task for information retrieval, which aims at identifying event
triggers and classifying them into pre-defined event types. In real-world applications, events …

This paper describes a novel algorithm to dynamically set endpointing thresholds based on
a rich set of dialogue features to detect the end of user utterances in a dialogue system. By …

Even as progress in speech technologies and task and dialog modeling has allowed the
development of advanced spoken dialog systems, the low-level interaction behavior of those …

This paper presents an experiment with three artificial agents adopting different strategies
when being interrupted by human conversational partners. The agent either ignored the …

Abstract Incremental Dialog Processing (IDP) enables Spoken Dialog Systems to gradually
process minimal units of user speech in order to give the user an early system response. In …

Dialogue management (DM) plays a key role in the quality of the interaction with the user in
a task-oriented dialogue system. In most existing approaches, the agent predicts only one …

Introducing Spoken Dialogue Systems into Intelligent Environments outlines the formalisms
of a novel knowledge-driven framework for spoken dialogue management and presents the …