End-to-End Task-Completion Neural Dialogue Systems

Understand

One of the major drawbacks of modularized task-completion dialogue systems is that each module is trained individually, which presents several challenges.

• For example, downstream modules are affected by earlier modules, and the performance of the entire system is not robust to the accumulated errors.
• This paper presents a novel end-to-end learning framework for task-completion dialogue systems to tackle such issues.
• Our neural dialogue system can directly interact with a structured database to assist users in accessing information and accomplishing certain tasks.