Lab Tutorial: Towards Open-domain Spoken Dialogue Systems

Опубликовано 22 июня 2016, 1:05

Virtually all current spoken dialogue systems are designed to operate in either a specific carefully defined domain such as restaurant information and appointment booking, or they have very limited conversational ability such as in Siri and Google Now. However, if voice is to become a significant input modality for accessing web-based information and services, then techniques will be needed to enable conversational spoken dialogue systems to operate within open domains. This talk will discuss methods by which current statistical approaches to spoken dialogue can be extended to cover much wider domains. In contrast to traditional rule-based approaches to building spoken dialogue systems (SDS), recent research has shown that it is possible to implement all of the required functionality using statistical models trained using a combination of supervised learning and reinforcement learning.