  This paper proposes an enhanced natural language generation system combining
the merits of both rule-based approaches and modern deep learning algorithms,
boosting its performance to the extent where the generated textual content is
capable of exhibiting agile human-writing styles and the content logic of which
is highly controllable. We also come up with a novel approach called HMCU to
measure the performance of the natural language processing comprehensively and
precisely.
