Abstract
Intent detection, also called intent classification or recognition, is an NLP technique to comprehend the purpose behind user utterances. This paper focuses on Multi-dialect Arabic intent detection in banking, utilizing the ArBanking77 dataset. Our method employs an ensemble of fine-tuned BERT-based models, integrating contrastive loss for training. To enhance generalization to diverse Arabic dialects, we augment the ArBanking77 dataset, originally in Modern Standard Arabic (MSA) and Palestinian, with additional dialects such as Egyptian, Moroccan, and Saudi, among others. Our approach achieved an F1-score of 0.8771, ranking first in subtask-1 of the AraFinNLP shared task 2024.- Anthology ID:
- 2024.arabicnlp-1.41
- Volume:
- Proceedings of The Second Arabic Natural Language Processing Conference
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Nizar Habash, Houda Bouamor, Ramy Eskander, Nadi Tomeh, Ibrahim Abu Farha, Ahmed Abdelali, Samia Touileb, Injy Hamed, Yaser Onaizan, Bashar Alhafni, Wissam Antoun, Salam Khalifa, Hatem Haddad, Imed Zitouni, Badr AlKhamissi, Rawan Almatham, Khalil Mrini
- Venues:
- ArabicNLP | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 441–445
- Language:
- URL:
- https://aclanthology.org/2024.arabicnlp-1.41
- DOI:
- Cite (ACL):
- Asmaa Ramadan, Manar Amr, Marwan Torki, and Nagwa El-Makky. 2024. MA at AraFinNLP2024: BERT-based Ensemble for Cross-dialectal Arabic Intent Detection. In Proceedings of The Second Arabic Natural Language Processing Conference, pages 441–445, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- MA at AraFinNLP2024: BERT-based Ensemble for Cross-dialectal Arabic Intent Detection (Ramadan et al., ArabicNLP-WS 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.arabicnlp-1.41.pdf