A Hybrid Natural Language Generation System Integrating Rules and Deep Learning Algorithms

Abstract

This paper proposes an enhanced natural language generation system combining the merits of both rulebased 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.