عنوان انگلیسی مقاله:
Emotional editing constraint conversation content generation based on reinforcement learning
ترجمه فارسی عنوان مقاله:
ویرایش احساسی تولید محتوای مکالمه محدود بر اساس یادگیری تقویتی
Sciencedirect - Elsevier - Information Fusion, 56 (2020) 70-80. doi:10.1016/j.inffus.2019.10.007
Xiao Sun a , 1 , ∗ , Jia Li a , 1 , Xing Wei a , Changliang Li b , Jianhua Tao c
In recent years, the generation of conversation content based on deep neural networks has attracted many re- searchers. However, traditional neural language models tend to generate general replies, lacking logical and emotional factors. This paper proposes a conversation content generation model that combines reinforcement learning with emotional editing constraints to generate more meaningful and customizable emotional replies. The model divides the replies into three clauses based on pre-generated keywords and uses the emotional editor to further optimize the final reply. The model combines multi-task learning with multiple indicator rewards to comprehensively optimize the quality of replies. Experiments shows that our model can not only improve the fluency of the replies, but also significantly enhance the logical relevance and emotional relevance of the replies.
Keywords: Emotional conversation generation | Affective computing | Emotional editing | Reinforcement learning | Multitask learning