From Theories on Styles to their Transfer in Text: Bridging the Gap with a Hierarchical Survey
Enrica Troiano, Aswathy Velutharambath, Roman Klinger

TL;DR
This paper provides a hierarchical survey of style transfer in natural language generation, categorizing styles into intentional and unintentional groups, and discusses challenges and future research directions.
Contribution
It introduces a hierarchical framework for classifying styles in text style transfer and analyzes current methods and research gaps within this structure.
Findings
Styles are categorized into two main groups: arbitrary modulation and unintentional expression.
The paper highlights challenges in defining and transferring different styles.
It identifies unexplored styles and suggests suitable methods for future research.
Abstract
Humans are naturally endowed with the ability to write in a particular style. They can, for instance, re-phrase a formal letter in an informal way, convey a literal message with the use of figures of speech or edit a novel by mimicking the style of some well-known authors. Automating this form of creativity constitutes the goal of style transfer. As a natural language generation task, style transfer aims at rewriting existing texts, and specifically, it creates paraphrases that exhibit some desired stylistic attributes. From a practical perspective, it envisions beneficial applications, like chatbots that modulate their communicative style to appear empathetic, or systems that automatically simplify technical articles for a non-expert audience. Several style-aware paraphrasing methods have attempted to tackle style transfer. A handful of surveys give a methodological overview of the…
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Taxonomy
TopicsTopic Modeling · AI in Service Interactions · Speech and dialogue systems
