A stochastic finite-state transducer approach to spoken dialog management

In this paper, we present an approach to spoken dialog management based on the use of a Stochastic Finite-State Transducer estimated from a dialog corpus. The states of the Stochastic Finite-State Transducer represent the dialog states, the input alphabet includes all the possible user utterances, without considering specific values, and the set of system answers constitutes the output alphabet. Then, a dialog describes a path in the transducer model from the initial state to the final one. An automatic dialog generation technique was used in order to generate the dialog corpus from which the transducer parameters are estimated. Our proposal for dialog management has been evaluated in a sport facilities booking task.