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Python Hidden Markov Model

This module provides an implementation of a hidden Markov model (HMM) for discrete observation variables. The module was written with two requirements

  1. Easy-to-follow code for teaching
  2. Ability to handle large datasets

For those learning about HMMs, I recommend following along with the Rabiner tutorial [1] as a reference for variable names and techniques implemented in this module. Finally, this software requires the NumPy and matplotlib modules.

Installation

There is no packaging of this software. Simply place hmm.py into your Python path.

Download

[HMMPy] Contains hmm.py module and Doxygen documentation.

References

[1]LR Rabiner. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 1989.

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