Intent Classifier

Intent classification aims to automatically determine the user's intention from text or speech input, a crucial task for applications like virtual assistants and automated systems. Current research focuses on improving accuracy and robustness, particularly in low-resource settings, using techniques like data augmentation with large language models (LLMs) and employing architectures such as Bi-LSTMs and deep reinforcement learning models. These advancements are significant for enhancing the performance and reliability of human-computer interaction systems across various domains, including healthcare, security, and e-commerce.