  Maintaining a consistent personality in conversations is quite natural for
human beings, but is still a non-trivial task for machines. The persona-based
dialogue generation task is thus introduced to tackle the
personality-inconsistent problem by incorporating explicit persona text into
dialogue generation models. Despite the success of existing persona-based
models on generating human-like responses, their one-stage decoding framework
can hardly avoid the generation of inconsistent persona words. In this work, we
introduce a three-stage framework that employs a generate-delete-rewrite
mechanism to delete inconsistent words from a generated response prototype and
further rewrite it to a personality-consistent one. We carry out evaluations by
both human and automatic metrics. Experiments on the Persona-Chat dataset show
that our approach achieves good performance.

Computation and Language