Scalable and Robust Conversational Systems - 2020

Explore a 51-minute lecture on enhancing conversational systems presented by Yun-Nung (Vivian) Chen from National Taiwan University. Delve into recent research focusing on analyzing bias in state-of-the-art models and learning language embeddings for practical scenarios with noisy inputs. Discover methods for building scalable systems using zero-shot learning and dual learning properties. Gain insights into improving the robustness and scalability of conversational AI, with potential implications for future research directions. Learn from Chen's expertise in spoken dialogue systems, language understanding, natural language processing, and multimodality, developed through her work at Carnegie Mellon University and Microsoft Research Redmond.