Explore Bayesian networks and their application to automatic speech recognition (ASR) in this seminar lecture delivered by Geoffrey Zweig from IBM's T.J. Watson Research Center. Learn about the fundamental algorithms and structural approaches used in Bayesian networks for speech recognition systems. Discover how probabilistic graphical models can be leveraged to improve ASR performance through sophisticated modeling techniques. Examine the theoretical foundations and practical implementations of Bayesian network architectures specifically designed for speech processing applications. Gain insights into the intersection of machine learning, probability theory, and speech technology from an industry research perspective.