2023
EMNLP
EMNLP 2023
Intent Detection and Slot Filling for Home Assistants: Dataset and Analysis for Bangla and Sylheti
Abstract
AbstractAs 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.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Natural Language Processing
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Keyword Pioneer
— speech assistant
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Hot Topic Early Bird
— bangla language
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Topics
Natural Language Processing > Applications > Intent Classification
Natural Language Processing > Resources & Methods > Large Language Models
Natural Language Processing > Resources & Methods > Multilingual NLP
Machine Learning > Learning Types > Few-Shot Learning
Natural Language Processing > Applications > Slot Filling
Artificial Intelligence > Core AI > Dialogue Systems