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Generating stylized responses is essential to build intelligent and engagingdialogue systems. However, this task is far from well-explored due to thedifficulties of rendering a particular style in coherent responses, especiallywhen the target style is embedded only in unpaired texts that cannot bedirectly used to train the dialogue model. This paper proposes a stylizeddialogue generation method that can capture stylistic features embedded inunpaired texts. Specifically, our method can produce dialogue responses thatare both coherent to the given context and conform to the target style. In thisstudy, an inverse dialogue model is first introduced to predict possible postsfor the input responses, and then this inverse model is used to generatestylized pseudo dialogue pairs based on these stylized unpaired texts. Further,these pseudo pairs are employed to train the stylized dialogue model with ajoint training process, and a style routing approach is proposed to intensifystylistic features in the decoder. Automatic and manual evaluations on twodatasets demonstrate that our method outperforms competitive baselines inproducing coherent and style-intensive dialogue responses.

Stylized Dialogue Response Generation Using Stylized Unpaired Texts