Md Mushfiqur Rahman


2023

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To token or not to token: A Comparative Study of Text Representations for Cross-Lingual Transfer
Md Mushfiqur Rahman | Fardin Ahsan Sakib | Fahim Faisal | Antonios Anastasopoulos
Proceedings of the 3rd Workshop on Multi-lingual Representation Learning (MRL)

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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
Proceedings of the First Workshop on Bangla Language Processing (BLP-2023)

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.