Abstract
This paper describes our system designed for SemEval-2023 Task 12: Sentiment analysis for African languages. The challenge faced by this task is the scarcity of labeled data and linguistic resources in low-resource settings. To alleviate these, we propose a generalized multilingual system SACL-XLMR for sentiment analysis on low-resource languages. Specifically, we design a lexicon-based multilingual BERT to facilitate language adaptation and sentiment-aware representation learning. Besides, we apply a supervised adversarial contrastive learning technique to learn sentiment-spread structured representations and enhance model generalization. Our system achieved competitive results, largely outperforming baselines on both multilingual and zero-shot sentiment classification subtasks. Notably, the system obtained the 1st rank on the zero-shot classification subtask in the official ranking. Extensive experiments demonstrate the effectiveness of our system.- Anthology ID:
- 2023.semeval-1.255
- Volume:
- Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1849–1857
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.255
- DOI:
- 10.18653/v1/2023.semeval-1.255
- Cite (ACL):
- Dou Hu, Lingwei Wei, Yaxin Liu, Wei Zhou, and Songlin Hu. 2023. UCAS-IIE-NLP at SemEval-2023 Task 12: Enhancing Generalization of Multilingual BERT for Low-resource Sentiment Analysis. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1849–1857, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- UCAS-IIE-NLP at SemEval-2023 Task 12: Enhancing Generalization of Multilingual BERT for Low-resource Sentiment Analysis (Hu et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/ingest-bitext-workshop/2023.semeval-1.255.pdf