Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation
Table 3: Human evaluation results on two datasets. Each cell indicates the proportion of being preferred.
['Model', 'Yelp Style', 'Yelp Content', 'Yelp Fluency', 'IMDb Style', 'IMDb Content', 'IMDb Fluency']
For the human evaluation, we choose two of the most well-performed models according to the automatic evaluation results as competitors: DeleteAndRetrieve (DAR) Li et al. Hu et al. And the generated outputs from multi-class discriminator model is used as our final model. We have performed over 400 human evaluation reviews. The human evaluation results are mainly conformed with our automatic evaluation results. And it also shows that our models are better in content preservation, compared to two competitor model.