Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 41-45).This thesis studies style transfer on the basis of non-parallel text. This is an instance of a broad family of problems including machine translation, decipherment, and attribute modication. The key challenge is to separate the content from style in an unsupervised manner. We assume a shared latent content distribution across different text corpora, and propose a method that leve...
We propose DGST, a novel and simple Dual-Generator network architecture for text Style Transfer. Our...
We present a general framework for unsupervised text style transfer with deep generative models. The...
Style is an integral part of natural language in written, spoken or machine generated forms. Humans ...
© 2017 Neural information processing systems foundation. All rights reserved. This paper focuses on ...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
The ability to transfer styles of texts or images, is an important measurement of the advancement of...
International audienceTextual style transfer involves modifying the style of a text while preserving...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
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...
The stylistic properties of text have intrigued computational linguistics researchers in recent year...
Controlling the style of natural language by disentangling the latent space is an important step to...
Text style transfer is an important task in natural language generation, which aims to control certa...
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...
We propose DGST, a novel and simple Dual-Generator network architecture for text Style Transfer. Our...
We present a general framework for unsupervised text style transfer with deep generative models. The...
Style is an integral part of natural language in written, spoken or machine generated forms. Humans ...
© 2017 Neural information processing systems foundation. All rights reserved. This paper focuses on ...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
The ability to transfer styles of texts or images, is an important measurement of the advancement of...
International audienceTextual style transfer involves modifying the style of a text while preserving...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
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...
The stylistic properties of text have intrigued computational linguistics researchers in recent year...
Controlling the style of natural language by disentangling the latent space is an important step to...
Text style transfer is an important task in natural language generation, which aims to control certa...
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...
We propose DGST, a novel and simple Dual-Generator network architecture for text Style Transfer. Our...
We present a general framework for unsupervised text style transfer with deep generative models. The...
Style is an integral part of natural language in written, spoken or machine generated forms. Humans ...