Text style transfer: A review and experimental evaluation
The stylistic properties of text have intrigued computational linguistics researchers in recent
years. Specifically, researchers have investigated the text style transfer task (TST), which …
years. Specifically, researchers have investigated the text style transfer task (TST), which …
Deep learning for text style transfer: A survey
Text style transfer is an important task in natural language generation, which aims to control
certain attributes in the generated text, such as politeness, emotion, humor, and many …
certain attributes in the generated text, such as politeness, emotion, humor, and many …
Reformulating unsupervised style transfer as paraphrase generation
Modern NLP defines the task of style transfer as modifying the style of a given sentence
without appreciably changing its semantics, which implies that the outputs of style transfer …
without appreciably changing its semantics, which implies that the outputs of style transfer …
Multiple-attribute text rewriting
The dominant approach to unsupervised" style transfer''in text is based on the idea of
learning a latent representation, which is independent of the attributes specifying its" style'' …
learning a latent representation, which is independent of the attributes specifying its" style'' …
Style transformer: Unpaired text style transfer without disentangled latent representation
Disentangling the content and style in the latent space is prevalent in unpaired text style
transfer. However, two major issues exist in most of the current neural models. 1) It is difficult …
transfer. However, two major issues exist in most of the current neural models. 1) It is difficult …
Transforming delete, retrieve, generate approach for controlled text style transfer
A Sudhakar, B Upadhyay, A Maheswaran - arXiv preprint arXiv …, 2019 - arxiv.org
Text style transfer is the task of transferring the style of text having certain stylistic attributes,
while preserving non-stylistic or content information. In this work we introduce the …
while preserving non-stylistic or content information. In this work we introduce the …
A dual reinforcement learning framework for unsupervised text style transfer
Unsupervised text style transfer aims to transfer the underlying style of text but keep its main
content unchanged without parallel data. Most existing methods typically follow two steps …
content unchanged without parallel data. Most existing methods typically follow two steps …
Generalized data augmentation for low-resource translation
Translation to or from low-resource languages LRLs poses challenges for machine
translation in terms of both adequacy and fluency. Data augmentation utilizing large …
translation in terms of both adequacy and fluency. Data augmentation utilizing large …
Expertise style transfer: A new task towards better communication between experts and laymen
The curse of knowledge can impede communication between experts and laymen. We
propose a new task of expertise style transfer and contribute a manually annotated dataset …
propose a new task of expertise style transfer and contribute a manually annotated dataset …
Unsupervised neural text simplification
The paper presents a first attempt towards unsupervised neural text simplification that relies
only on unlabeled text corpora. The core framework is composed of a shared encoder and a …
only on unlabeled text corpora. The core framework is composed of a shared encoder and a …