Exploring Cross-lingual Textual Style Transfer with Large Multilingual Language Models

06/05/2022
by   Daniil Moskovskiy, et al.
0

Detoxification is a task of generating text in polite style while preserving meaning and fluency of the original toxic text. Existing detoxification methods are designed to work in one exact language. This work investigates multilingual and cross-lingual detoxification and the behavior of large multilingual models like in this setting. Unlike previous works we aim to make large language models able to perform detoxification without direct fine-tuning in given language. Experiments show that multilingual models are capable of performing multilingual style transfer. However, models are not able to perform cross-lingual detoxification and direct fine-tuning on exact language is inevitable.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/08/2021

Uppsala NLP at SemEval-2021 Task 2: Multilingual Language Models for Fine-tuning and Feature Extraction in Word-in-Context Disambiguation

We describe the Uppsala NLP submission to SemEval-2021 Task 2 on multili...
research
04/19/2022

Detecting Text Formality: A Study of Text Classification Approaches

Formality is an important characteristic of text documents. The automati...
research
06/05/2023

Exploring the Relationship between Alignment and Cross-lingual Transfer in Multilingual Transformers

Without any explicit cross-lingual training data, multilingual language ...
research
05/03/2023

Identifying the Correlation Between Language Distance and Cross-Lingual Transfer in a Multilingual Representation Space

Prior research has investigated the impact of various linguistic feature...
research
06/27/2023

GenerTTS: Pronunciation Disentanglement for Timbre and Style Generalization in Cross-Lingual Text-to-Speech

Cross-lingual timbre and style generalizable text-to-speech (TTS) aims t...
research
08/31/2021

Cross-Lingual Text Classification of Transliterated Hindi and Malayalam

Transliteration is very common on social media, but transliterated text ...
research
04/13/2021

Zhestyatsky at SemEval-2021 Task 2: ReLU over Cosine Similarity for BERT Fine-tuning

This paper presents our contribution to SemEval-2021 Task 2: Multilingua...

Please sign up or login with your details

Forgot password? Click here to reset