Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti
Fardin Ahsan Sakib, A H M Rezaul Karim, Saadat Hasan Khan, Md Mushfiqur Rahman
Abstract
As voice assistants cement their place in our technologically advanced society, there remains a need to cater to the diverse linguistic landscape, including colloquial forms of low-resource languages. Our study introduces the first-ever comprehensive dataset for intent detection and slot filling in formal Bangla, colloquial Bangla, and Sylheti languages, totaling 984 samples across 10 unique intents. Our analysis reveals the robustness of large language models for tackling downstream tasks with inadequate data. The GPT-3.5 model achieves an impressive F1 score of 0.94 in intent detection and 0.51 in slot filling for colloquial Bangla.- Anthology ID:
- 2023.banglalp-1.6
- Volume:
- Proceedings of the First Workshop on Bangla Language Processing (BLP-2023)
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Firoj Alam, Sudipta Kar, Shammur Absar Chowdhury, Farig Sadeque, Ruhul Amin
- Venue:
- BanglaLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 48–55
- Language:
- URL:
- https://aclanthology.org/2023.banglalp-1.6
- DOI:
- 10.18653/v1/2023.banglalp-1.6
- Cite (ACL):
- Fardin Ahsan Sakib, A H M Rezaul Karim, Saadat Hasan Khan, and Md Mushfiqur Rahman. 2023. Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti. In Proceedings of the First Workshop on Bangla Language Processing (BLP-2023), pages 48–55, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti (Sakib et al., BanglaLP 2023)
- PDF:
- https://preview.aclanthology.org/landing_page/2023.banglalp-1.6.pdf