  We participate in the DSTC9 Interactive Dialogue Evaluation Track (Gunasekara
et al. 2020) sub-task 1 (Knowledge Grounded Dialogue) and sub-task 2
(Interactive Dialogue). In sub-task 1, we employ a pre-trained language model
to generate topic-related responses and propose a response ensemble method for
response selection. In sub-task2, we propose a novel Dialogue Planning Model
(DPM) to capture conversation flow in the interaction with humans. We also
design an integrated open-domain dialogue system containing pre-process,
dialogue model, scoring model, and post-process, which can generate fluent,
coherent, consistent, and humanlike responses. We tie 1st on human ratings and
also get the highest Meteor, and Bert-score in sub-task 1, and rank 3rd on
interactive human evaluation in sub-task 2.
