HausaNLP at SemEval-2024 Task 1: Textual Relatedness Analysis for Semantic Representation of Sentences

Saheed Abdullahi Salahudeen, Falalu Ibrahim Lawan, Yusuf Aliyu, Amina Abubakar, Lukman Aliyu, Nur Rabiu, Mahmoud Ahmad, Aliyu Rabiu Shuaibu, Alamin Musa


Abstract
Semantic Text Relatedness (STR), a measure of meaning similarity between text elements, has become a key focus in the field of Natural Language Processing (NLP). We describe SemEval-2024 task 1 on Semantic Textual Relatedness featuring three tracks: supervised learning, unsupervised learning and cross-lingual learning across African and Asian languages including Afrikaans, Algerian Arabic, Amharic, Hausa, Hindi, Indonesian, Kinyarwanda, Marathi, Moroccan Arabic, Modern Standard Arabic, Punjabi, Spanish, and Telugu. Our goal is to analyse the semantic representation of sentences textual relatedness trained on mBert, all-MiniLM-L6-v2 and Bert-Based-uncased. The effectiveness of these models is evaluated using the Spearman Correlation metric, which assesses the strength of the relationship between paired data. The finding reveals the viability of transformer models in multilingual STR tasks.
Anthology ID:
2024.semeval-1.29
Volume:
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
188–192
Language:
URL:
https://aclanthology.org/2024.semeval-1.29
DOI:
Bibkey:
Cite (ACL):
Saheed Abdullahi Salahudeen, Falalu Ibrahim Lawan, Yusuf Aliyu, Amina Abubakar, Lukman Aliyu, Nur Rabiu, Mahmoud Ahmad, Aliyu Rabiu Shuaibu, and Alamin Musa. 2024. HausaNLP at SemEval-2024 Task 1: Textual Relatedness Analysis for Semantic Representation of Sentences. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 188–192, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
HausaNLP at SemEval-2024 Task 1: Textual Relatedness Analysis for Semantic Representation of Sentences (Salahudeen et al., SemEval 2024)
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PDF:
https://preview.aclanthology.org/ingestion-checklist/2024.semeval-1.29.pdf
Supplementary material:
 2024.semeval-1.29.SupplementaryMaterial.txt
Supplementary material:
 2024.semeval-1.29.SupplementaryMaterial.zip