Low-Resource Text Style Transfer for Bangla: Data & Models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A10475865" target="_blank" >RIV/00216208:11320/23:10475865 - isvavai.cz</a>

Výsledek na webu

<a href="https://aclanthology.org/2023.banglalp-1.5/" target="_blank" >https://aclanthology.org/2023.banglalp-1.5/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.18653/v1/2023.banglalp-1.5" target="_blank" >10.18653/v1/2023.banglalp-1.5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Low-Resource Text Style Transfer for Bangla: Data & Models

Popis výsledku v původním jazyce

Text style transfer (TST) involves modifying the linguistic style of a given text while retaining its core content. This paper addresses the challenging task of text style transfer in the Bangla language, which is low-resourced in this area. We present a novel Bangla dataset that facilitates text sentiment transfer, a subtask of TST, enabling the transformation of positive sentiment sentences to negative and vice versa. To establish a high-quality base for further research, we refined and corrected an existing English dataset of 1,000 sentences for sentiment transfer based on Yelp reviews, and we introduce a new human-translated Bangla dataset that parallels its English counterpart. Furthermore, we offer multiple benchmark models that serve as a validation of the dataset and baseline for further research.

Název v anglickém jazyce

Low-Resource Text Style Transfer for Bangla: Data & Models

Popis výsledku anglicky

Text style transfer (TST) involves modifying the linguistic style of a given text while retaining its core content. This paper addresses the challenging task of text style transfer in the Bangla language, which is low-resourced in this area. We present a novel Bangla dataset that facilitates text sentiment transfer, a subtask of TST, enabling the transformation of positive sentiment sentences to negative and vice versa. To establish a high-quality base for further research, we refined and corrected an existing English dataset of 1,000 sentences for sentiment transfer based on Yelp reviews, and we introduce a new human-translated Bangla dataset that parallels its English counterpart. Furthermore, we offer multiple benchmark models that serve as a validation of the dataset and baseline for further research.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the First Workshop on Bangla Language Processing

ISBN

979-8-89176-058-5

ISSN

—

e-ISSN

—

Počet stran výsledku

14

Strana od-do

34-47

Název nakladatele

Association for Computational Linguistics

Místo vydání

Stroudsburg, PA, USA

Místo konání akce

Singapore, Singapore

Datum konání akce

7. 12. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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