TECHSSN at SemEval-2024 Task 1: Multilingual Analysis for Semantic Textual Relatedness using Boosted Transformer Models
Shreejith Babu G, Ravindran V, Aashika Jetti, Rajalakshmi Sivanaiah, Angel Deborah
Abstract
This paper presents our approach to SemEval- 2024 Task 1: Semantic Textual Relatedness (STR). Out of the 14 languages provided, we specifically focused on English and Telugu. Our proposal employs advanced natural language processing techniques and leverages the Sentence Transformers library for sentence embeddings. For English, a Gradient Boosting Regressor trained on DistilBERT embeddingsachieves competitive results, while for Telugu, a multilingual model coupled with hyperparameter tuning yields enhanced performance. The paper discusses the significance of semantic relatedness in various languages, highlighting the challenges and nuances encountered. Our findings contribute to the understanding of semantic textual relatedness across diverse linguistic landscapes, providing valuable insights for future research in multilingual natural language processing.- Anthology ID:
- 2024.semeval-1.130
- 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:
- 907–912
- Language:
- URL:
- https://aclanthology.org/2024.semeval-1.130
- DOI:
- Cite (ACL):
- Shreejith Babu G, Ravindran V, Aashika Jetti, Rajalakshmi Sivanaiah, and Angel Deborah. 2024. TECHSSN at SemEval-2024 Task 1: Multilingual Analysis for Semantic Textual Relatedness using Boosted Transformer Models. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 907–912, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- TECHSSN at SemEval-2024 Task 1: Multilingual Analysis for Semantic Textual Relatedness using Boosted Transformer Models (Babu G et al., SemEval 2024)
- PDF:
- https://preview.aclanthology.org/ingestion-checklist/2024.semeval-1.130.pdf