The Baum-Welch Algorithm#
Leonard Baum adn Lloyd Welch#
The Baum-Welch algorithm was developed by Leonard E. Baum and Lloyd R. Welch in the late 1960s and early 1970s. Leonard Baum, a mathematician, and Lloyd Welch, a statistician, both worked at the Institute for Defense Analyses (IDA) at Princeton, New Jersey. Their work contributed significantly to the theory of Hidden Markov Models (HMMs), particularly in developing this expectation-maximization algorithm to estimate the unknown parameters of HMMs.
Their work, specifically on this algorithm, was part of a broader set of contributions in the study of probabilistic models and statistical inference, particularly in applications related to communication systems, speech recognition, and signal processing.
The Baum-Welch algorithm is often cited from their paper titled “A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains” (1970), which laid the foundation for this widely used approach in machine learning and statistical modeling.