However the progress in language style transfer is lagged behind other domains such as computer vision mainly because of the lack of parallel data and principle evaluation metrics.

What is text style transfer. Unsupervised Text Style Transfer using Language Models as Discriminators Zichao Yang 1 Zhiting Hu Chris Dyer2 Eric P. However this is under-explored in the NLP commu-nity. Style Transfer in Text.

Despite the success existing works have achieved using a parallel corpus for the two styles transferring text style has proven significantly more challenging when there is no parallel training corpus. Recent style transfer methods have considered texture control to enhance usability. However controlling the stylistic degree in terms of shape deformation remains an important open challenge.

Text style transfer TST is an important task in natural language generation NLG which aims to control certain attributes in the generated text such as politeness emotion humor. Through the effects of color texture light shade and additional deco-rative elements the artistic texts can strengthen the impression and convey more semantic. Artistic text style transfer is the task of migrating the style from a source image to the target text to create artistic typography.

2017 proposes an expression to distinguish style and content of a picture. A number of recent machine learning papers work with an automated style transfer for texts and counter to intuition demonstrate that there is no consensus formulation of this NLP task. Style Transfer from Non-Parallel Text by Cross-Alignment NIPS-2017 Adversarially Regularized Autoencoders ICML-2018 Zero-Shot Style Transfer in Text Using Recurrent Neural Networks Arxiv-2017 Style Transfer in Text.

Since the definition of the text style is vague it is difficult to construct paired sen-tences with the same content and differing styles. How to separate content from style in text remains an open research problem in text style transfer. Index Termstext style transfer decorative elements extrac-tion decoration re-composition I.

Sentiment politeness into a target style while otherwise changing as little as possible about the input. Many types of style transfer can be performed with only small precise edits instead of. In computer vision Li et al.