An empirical assessment of deep learning approaches to task-oriented dialog management

Task-oriented spoken dialog system for second-language learning

This paper introduces a Dialog-Based Computer Assisted secondLanguage Learning (DB-CALL) system using task-oriented dialogue processing technology. The system promotes dialogue with a second-language learner for a specific task, such as purchasing tour tickets, ordering food, passing through immigration, etc. The dialog system plays a role of a ticket agent, a waiter, or an immigration officer ...

Task-Based Dialog Management Using An Agenda

Dialog man tigement addresses two specific problems: (1) providing a coherent overall structure to interaction that extends beyond the single turn, (2) correctly managing mixedinitiative interaction. We propose a dialog management architecture based on the following elements: handlers that manage interaction focussed on tightly coupled sets of information, a product that reflects mutually agree...

Recent Approaches to Dialog Management for Spoken Dialog Systems

Learning End-to-End Goal-Oriented Dialog

End-to-end dialog systems, in which all components are learnt simultaneously, have recently obtained encouraging successes. However these were mostly on conversations related to chit-chat with no clear objective and for which evaluation is difficult. This paper proposes a set of tasks to test the capabilities of such systems on goal-oriented dialogs, where goal completion ensures a well-defined...

Incremental dialog processing in a task-oriented dialog

Incremental Dialog Processing (IDP) enables Spoken Dialog Systems to gradually process minimal units of user speech in order to give the user an early system response. In this paper, we present an application of IDP that shows its effectiveness in a task-oriented dialog system. We have implemented an IDP strategy and deployed it for one month on a real-user system. We compared the resulting dia...