Speech Modeling

Speech modeling aims to create computational representations of spoken language, enabling tasks like speech recognition, enhancement, and understanding. Current research focuses on developing sophisticated generative models, such as variational autoencoders (VAEs) and transformers, often incorporating hierarchical structures and leveraging techniques like random features for efficient computation. These advancements are improving the accuracy and efficiency of speech processing applications, particularly in areas like pathological speech analysis and spoken language understanding, leading to better diagnostic tools and more robust human-computer interaction.