  Text style transfer is a hot issue in recent natural language
processing,which mainly studies the text to adapt to different specific
situations, audiences and purposes by making some changes. The style of the
text usually includes many aspects such as morphology, grammar, emotion,
complexity, fluency, tense, tone and so on. In the traditional text style
transfer model, the text style is generally relied on by experts knowledge and
hand-designed rules, but with the application of deep learning in the field of
natural language processing, the text style transfer method based on deep
learning Started to be heavily researched. In recent years, text style transfer
is becoming a hot issue in natural language processing research. This article
summarizes the research on the text style transfer model based on deep learning
in recent years, and summarizes, analyzes and compares the main research
directions and progress. In addition, the article also introduces public data
sets and evaluation indicators commonly used for text style transfer. Finally,
the existing characteristics of the text style transfer model are summarized,
and the future development trend of the text style transfer model based on deep
learning is analyzed and forecasted.
