تقرير
Semi-supervised Text Style Transfer: Cross Projection in Latent Space
| العنوان: | Semi-supervised Text Style Transfer: Cross Projection in Latent Space |
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| المؤلفون: | Shang, Mingyue, Li, Piji, Fu, Zhenxin, Bing, Lidong, Zhao, Dongyan, Shi, Shuming, Yan, Rui |
| سنة النشر: | 2019 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language |
| الوصف: | Text style transfer task requires the model to transfer a sentence of one style to another style while retaining its original content meaning, which is a challenging problem that has long suffered from the shortage of parallel data. In this paper, we first propose a semi-supervised text style transfer model that combines the small-scale parallel data with the large-scale nonparallel data. With these two types of training data, we introduce a projection function between the latent space of different styles and design two constraints to train it. We also introduce two other simple but effective semi-supervised methods to compare with. To evaluate the performance of the proposed methods, we build and release a novel style transfer dataset that alters sentences between the style of ancient Chinese poem and the modern Chinese. Comment: EMNLP 2019 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1909.11493 |
| رقم الأكسشن: | edsarx.1909.11493 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |