Natural　language　generation　is　an　important　part　of　artificial　intelligence　system.　As　artificial　intelligence　technology　is　gradually　integrated　into　human　lives,　people　have　higher　requirements　for　natural　language　generation　technology,　and　controllable　natural　language　generation　has　become　a　new　research　hotspot.　The　task　of　text　style　transfer,　as　an　important　research　direction　of　controllable　natural　language　generation,　has　been　widely　concerned　by　academia　and　industry.　The　task　of　text　style　transfer　refers　to　the　purposeful　generation　of　target-style　sentences　on　the　basis　of　retaining　the　original　content　of　the　text.　To　further　demonstrate　the　development　process　of　this　task,　the　definition　and　development　context　of　the　current　text　style　transfer　task　was　first　introduced.　Then,　based　on　the　model　method,　the　current　research　work　was　summarized　into　three　categories:　based　on　latent　space　disentangled,　and　based　on　explicit　disentangled,　based　on　one-step　mapping,　and　on　the　basis　of　a　brief　description　of　these　works,　enlightening　work　was　focused　on.　Furthermore,　the　common　data　sets　and　evaluation　methods　in　the　text　style　transfer　task　was　combed　and　analyzed.　Finally　the　future　development　trend　of　the　text　style　transfer　task　was　prospected.　©　2022,　Editorial　Department　of　Journal　of　Beijing　University　of　Technology.　All　right　reserved.