Statistical user simulation is a promising methodology to train and evaluate the performance of (spoken) dialog systems. We work with a modular architecture for data-driven simula...
We describe work done at three sites on designing conversational agents capable of incremental processing. We focus on the `middleware' layer in these systems, which takes ca...
David Schlangen, Timo Baumann, Hendrik Buschmeier,...
This paper introduces a new dialogue management framework for goal-directed conversations. A declarative specification defines the domain-specific elements and guides the dialogue...
Two of the main corpora available for training discourse relation classifiers are the RST Discourse Treebank (RST-DT) and the Penn Discourse Treebank (PDTB), which are both based ...
Hugo Hernault, Danushka Bollegala, Mitsuru Ishizuk...
This paper presents an agenda-based user simulator which has been extended to be trainable on real data with the aim of more closely modelling the complex rational behaviour exhib...
This paper presents a dialogue system in the form of an ECA that acts as a sociable and emotionally intelligent companion for the user. The system dialogue is not task-driven but ...
Marc Cavazza, Raul Santos de la Camara, Markku Tur...
This paper proposes a novel approach for predicting user satisfaction transitions during a dialogue only from the ratings given to entire dialogues, with the aim of reducing the c...
In spoken communications, correction utterances, which are utterances correcting other participants utterances and behaviors, play crucial roles, and detecting them is one of the ...
In this paper we examine the influence of dimensionality on natural language route directions in dialogue. Specifically, we show that giving route instructions in a quasi-3d envir...
Vivien Mast, Jan Smeddinck, Anna Strotseva, Thora ...