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...
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...
Spoken multimodal dialogue systems in which users address faceonly or embodied interface agents have been gaining ground in research for some time. Although most systems are still...
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. ...
Reinforcement techniques have been successfully used to maximise the expected cumulative reward of statistical dialogue systems. Typically, reinforcement learning is used to estim...