We propose DGST, a novel and simple Dual-Generator network architecture for text Style Transfer. Our model employs two generators only, and does not rely on any discriminators or parallel corpus for training. Both quantitative and qualitative experiments on the Yelp and IMDb datasets show that our model gives competitive performance compared to several strong baselines with more complicated architecture designs
Text effects transfer technology automatically makes the text dramatically more impressive. However,...
Text style transfer is an important task in controllable language generation. Supervised approaches ...
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Comput...
We propose DGST, a novel and simple Dual-Generator network architecture for text Style Transfer. Our...
Text Style Transfer, the process of transforming text from one style to another, has gained signific...
Text Style Transfer, the process of transforming text from one style to another, has gained signific...
Text style transfer is an important task in natural language generation, which aims to control certa...
The ability to transfer styles of texts or images, is an important measurement of the advancement of...
The stylistic properties of text have intrigued computational linguistics researchers in recent year...
Neural Style Transfer refers to the task of generating new outputs by combining the content from one...
We present a general framework for unsupervised text style transfer with deep generative models. The...
Text style transfer (TST) involves transforming a text into a desired style while approximately pres...
Recent studies show that auto-encoder based approaches successfully perform language generation, smo...
Text-based style transfer is a newly-emerging research topic that uses text information instead of s...
With the rapid growth of big multimedia data, multimedia processing techniques are facing some chall...
Text effects transfer technology automatically makes the text dramatically more impressive. However,...
Text style transfer is an important task in controllable language generation. Supervised approaches ...
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Comput...
We propose DGST, a novel and simple Dual-Generator network architecture for text Style Transfer. Our...
Text Style Transfer, the process of transforming text from one style to another, has gained signific...
Text Style Transfer, the process of transforming text from one style to another, has gained signific...
Text style transfer is an important task in natural language generation, which aims to control certa...
The ability to transfer styles of texts or images, is an important measurement of the advancement of...
The stylistic properties of text have intrigued computational linguistics researchers in recent year...
Neural Style Transfer refers to the task of generating new outputs by combining the content from one...
We present a general framework for unsupervised text style transfer with deep generative models. The...
Text style transfer (TST) involves transforming a text into a desired style while approximately pres...
Recent studies show that auto-encoder based approaches successfully perform language generation, smo...
Text-based style transfer is a newly-emerging research topic that uses text information instead of s...
With the rapid growth of big multimedia data, multimedia processing techniques are facing some chall...
Text effects transfer technology automatically makes the text dramatically more impressive. However,...
Text style transfer is an important task in controllable language generation. Supervised approaches ...
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Comput...