In the past decade, goal-oriented spoken dialogue systems have been the most prominent component in today’s virtual personal assistants. The classic dialogue systems have rather complex and/or modular pipelines. The advance of deep learning technologies has recently risen the applications of neural models to dialogue modeling. However, how to successfully apply deep learning based approaches to...

We present the dialogue module of the speech-to-speech translation system VERBMOBIL. We follow the approach that the solution to dialogue processing in a mediating scenario can not depend on a single constrained processing tool, but on a combination of several simple, efficient, and robust components. We show how our solution to dialogue processing works when applied to real data, and give some...

Two key objectives of conversational case-based reasoning (CCBR) systems are (1) eliciting case facts in a manner that minimizes the user’s burden in terms of resources such as time, information cost, and cognitive load, and (2) integrating CBR with other problem solving modalities. This paper proposes an architecture that addresses both these goals by integrating CBR with a discourse-oriented ...

What would you say if your refrigerator told you, " You're having some friends round for hot chocolate later. Maybe you should order two cartons of milk " ? Of course, in Spoken Dialogue Technology, Michael McTear will not give an answer to the question of whether talking to domestic appliances makes sense, but he indicates that even a normal household, for instance, may offer a wide field of a...

This paper describes how a multimodal dialogue application framework can be used to implement specific mobile applications and dynamic HTTP-based REST services. REST services are already publicly available and provide useful location-based information for the user on the go. We use a distributed, ontology-based dialogue system architecture where every major component can be run on a different h...

This work proposes a software component approach to design a dialogue multiagent system.

The application of machine learning methods to the dialogue management component of spoken dialogue systems is a growing research area. Whereas traditional methods use handcrafted rules to specify a dialogue policy, machine learning techniques seek to learn dialogue behaviours from a corpus of training data. In this paper, we identify the properties of a corpus suitable for training machine-lea...