We present a data-driven approach to learn user-adaptive referring expression generation (REG) policies for spoken dialogue systems. Referring expressions can be difficult to unde...
This paper presents a new framework for accumulating beliefs in spoken dialogue systems. The technique is based on updating a Bayesian Network that represents the underlying state...
Repair or error-recovery strategies are an important design issue in Spoken Dialogue Systems (SDSs) - how to conduct the dialogue when there is no progress (e.g. due to repeated A...
We present new results from a real-user evaluation of a data-driven approach to learning user-adaptive referring expression generation (REG) policies for spoken dialogue systems. ...