Inspired by the success of the data-driven approach, one can prepare a corpus of conversations for every possible style and feed it to a seq2seq.
in order to obtain a stylistically consistent DRG system through a vanilla seq2seq, this method requires millions of training instances for each target style, which is prohibitively expensive.