Learning to Plan and Realize Separately for Open-Ended Dialogue Systems

Sashank Santhanam, Zhuo Cheng, Brodie Mather, Bonnie J Dorr, Archna Bhatia, Bryanna Hebenstreit, Alan Zemel, Adam Dalton, Tomek Strzalkowski, Samira Shaikh

Abstract:

Achieving true human-like ability to conduct a conversation remains an elusive goal for open-ended dialogue systems. We posit this is because extant approaches towards natural language generation (NLG) are typically con- strued as end-to-end architectures that do not adequately model human generation processes. To investigate, we decouple generation into two separate phases: planning and realization. In the planning phase, we train two planners to generate plans for response utterances. The realization phase uses response plans to pro- duce an appropriate response. Through rigor- ous evaluations, both automated and human, we demonstrate that decoupling the process into planning and realization performs better than an end-to-end approach.