Text Style Transfer: An Introductory Overview

Fuente: arXiv
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Auteurs principaux: Mukherjee, Sourabrata, Dušek, Ondrej
Format: Preprint
Publié: 2024
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author Mukherjee, Sourabrata
Dušek, Ondrej
author_facet Mukherjee, Sourabrata
Dušek, Ondrej
contents Text Style Transfer (TST) is a pivotal task in natural language generation to manipulate text style attributes while preserving style-independent content. The attributes targeted in TST can vary widely, including politeness, authorship, mitigation of offensive language, modification of feelings, and adjustment of text formality. TST has become a widely researched topic with substantial advancements in recent years. This paper provides an introductory overview of TST, addressing its challenges, existing approaches, datasets, evaluation measures, subtasks, and applications. This fundamental overview improves understanding of the background and fundamentals of text style transfer.
format Preprint
id arxiv_https___arxiv_org_abs_2407_14822
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Text Style Transfer: An Introductory Overview
Mukherjee, Sourabrata
Dušek, Ondrej
Computation and Language
Text Style Transfer (TST) is a pivotal task in natural language generation to manipulate text style attributes while preserving style-independent content. The attributes targeted in TST can vary widely, including politeness, authorship, mitigation of offensive language, modification of feelings, and adjustment of text formality. TST has become a widely researched topic with substantial advancements in recent years. This paper provides an introductory overview of TST, addressing its challenges, existing approaches, datasets, evaluation measures, subtasks, and applications. This fundamental overview improves understanding of the background and fundamentals of text style transfer.
title Text Style Transfer: An Introductory Overview
topic Computation and Language
url https://arxiv.org/abs/2407.14822