Skill Routing

Skill routing directs user requests in large-scale conversational AI systems to the appropriate processing "skill" (e.g., playing music, providing weather updates). Current research focuses on improving the robustness and scalability of skill routing, particularly addressing the challenges posed by the long-tail distribution of user requests (infrequent queries). This involves developing self-learning methods that leverage user interactions to refine routing models, often employing encoder-decoder architectures and techniques like data augmentation to handle imbalanced datasets. Effective skill routing is crucial for enhancing the user experience and efficiency of conversational AI systems.