Sequential data often possesses hierarchical structures with complex dependencies
between sub-sequences, such as found between the utterances in a dialogue. To model …

We introduce a new class of models called multiresolution recurrent neural networks, which
explicitly model natural language generation at multiple levels of abstraction. The models …

Appropriate human likeness for social robots is said to increase trust and acceptance.
Whether this applies to human communication features like dialog initiative needs to be …

Aim Given a set of pre-defined medical categories used in Evidence Based Medicine, we
aim to automatically annotate sentences in medical abstracts with these labels. Method We …

Scripts represent knowledge of stereotypical event sequences that can aid text
understanding. Initial statistical methods have been developed to learn probabilistic scripts …

The past decade has seen a revolution in the field of spoken dialogue systems. As in other
areas of Computer Science and Artificial Intelligence, data-driven methods are now being …

A field of spoken dialog systems is a rapidly growing research area because the
performance improvement of speech technologies motivates the possibility of building …

Topic segmentation and labeling is often considered a prerequisite for higher-level
conversation analysis and has been shown to be useful in many Natural Language …

While end-to-end neural conversation models have led to promising advances in reducing
hand-crafted features and errors induced by the traditional complex system architecture …

Identifying effective tutorial dialogue strategies is a key issue for intelligent tutoring systems
research. Human-human tutoring offers a valuable model for identifying effective tutorial …