Editing Hidden Markov Models in Speech Synthesis (section)

==== Parameter Estimation Methods ====
# Maximum Likelihood Estimation (MLE): Employing MLE to estimate parameters like state transition and emission probabilities, enhancing model fitting accuracy. [Rabiner and Juang, 1986]<ref>Rabiner, L. R., & Juang, B. H. (1986). [https://ieeexplore.ieee.org/document/18626 An introduction to hidden Markov models]. IEEE ASSP Magazine, 3(1), 4-16.</ref>
# Baum-Welch Algorithm: Utilizing the Baum-Welch algorithm for iterative parameter estimation, maximizing the likelihood function of observed data. [Baum et al., 1970]<ref>- Baum, L. E., Petrie, T., Soules, G., & Weiss, N. (1970). [https://doi.org/10.1002/j.1538-7305.1970.tb01790.x A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains]. The annals of mathematical statistics, 41(1), 164-171.</ref>