This tutorial surveys neural approaches to conversational AI that were developed in the last
few years. We group conversational systems into three categories:(1) question answering …

This paper surveys the current state of the art in Natural Language Generation (NLG),
defined as the task of generating text or speech from non-linguistic input. A survey of NLG is …

In recent years some researchers have explored the use of reinforcement learning (RL)
algorithms as key components in the solution of various natural language processing (NLP) …

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 …

Conversations provide rich opportunities for interactive, continuous learning. When
something goes wrong, a system can ask for clarification, rewording, or otherwise redirect …

Spoken content retrieval refers to directly indexing and retrieving spoken content based on
the audio rather than text descriptions. This potentially eliminates the requirement of …

We present and evaluate a new model for Natural Language Generation (NLG) in Spoken
Dialogue Systems, based on statistical planning, given noisy feedback from the current …

This paper proposes a domain-independent statistical methodology to develop dialog
managers for spoken dialog systems. Our methodology employs a data-driven classification …

This paper targets the problem of speech act detection in conversations about bug repair.
We conduct a``Wizard of Oz''experiment with 30 professional programmers, in which the …

Research at the Interaction Lab focuses on human-agent communication using
conversational Natural Language. The ultimate goal is to create systems where humans and …