Accès ouvert

NLP-LISAC at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis via a Transformer-based Approach and Data Augmentation

Article scientifique 2023 Anglais

Résumé

This paper presents our system and findings for SemEval 2023 Task 9 Tweet Intimacy Analysis.The main objective of this task was to predict the intimacy of tweets in 10 languages.Our submitted model (ranked 28/45) consists of a transformer-based approach with data augmentation via machine translation.

Citer ce document

Benlahbib, A., Alami, H., Boumhidi, A., Benslimane, O. (2023). NLP-LISAC at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis via a Transformer-based Approach and Data Augmentation. https://doi.org/10.18653/v1/2023.semeval-1.16

Accès au document

Voir sur le dépôt source

Ce document est hébergé sur son dépôt institutionnel d'origine.

Statistiques

Consultations : 1

Téléchargements : 0