Language style transfer
Name
1051460721-MIT.pdf
Description
Full printable version
Size
351.75 KB
Format
Adobe PDF
Checksum (MD5)
a167603483e3d5169d00a88eda65e6c6
Author(s)
Shen, Tianxiao
Advisor(s)
Regina Barzilay.
Date Issued
2018
Publisher
Massachusetts Institute of Technology
Abstract
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 leverages refined alignment of latent representations to perform style transfer. The transferred sentences from one style should match example sentences from the other style as a population. To demonstrate the flexibility of the proposed model, we test it on three tasks: sentiment modication, decipherment of word substitution ciphers, and word order recovery. In both automatic and human evaluation our method achieves strong performance.
Description
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).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Persistent DSpace Link
