Evaluating style modification in text

In this thesis, we identify best practices for evaluating style modification, or style transfer, for text. Research of style transfer is bottlenecked by a lack of standard evaluation practices. We define three key aspects of interest (style transfer intensity, content preservation, and naturalness) and show how to obtain more reliable measures of them from human evaluation than in previous work. We also demonstrate stronger correlation between human judgment and a new set of automated metrics: the Wasserstein distance, word mover's distance on texts with style masked out, and adversarial classification for the respective aspects. Lastly, we illustrate aspect tradeoff curves for three state-of-the-art style transfer models to highlight the importance of evaluating style transfer models at specific points on the curves. This can enable direct comparison of the models, facilitating future research in style transfer.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2018

Author dc:creator

• Mir, Remi

Advisor dc:contributor.advisor

• Iyad Rahwan.

• Electrical Engineering and Computer Science.

Statement dc:rights

• 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/119569

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/119569