Probabilistic Independence Networks for Hidden Markov Probability Models

This chapter contains sections titled: Introduction, Notation and Background, Probabilistic Independence Networks, Modeling HMMs as PINs, Inference and MAP Algorithms for DPINs, Inference and MAP Calculations in HMM(1,1), Inference and MAP Algorithms for UPINs, More Complex HMMs for Speech Modeling, Learning and PINs, Summary, Appendix A: The Forward-Backward Algorithm for HMM(l,l) Is a Special Case of the JLO Algorithm, Appendix B: The Viterbi Algorithm for HMM(1,1) Is a Special Case of Dawid's Algorithm., Acknowledgments, References