Python: Real World Machine Learning

Building Hidden Markov Models

We are now ready to discuss speech recognition. We will use Hidden Markov Models (HMMs) to perform speech recognition. HMMs are great at modeling time series data. As an audio signal is a time series signal, HMMs perfectly suit our needs. An HMM is a model that represents probability distributions over sequences of observations. We assume that the outputs are generated by hidden states. So, our goal is to find these hidden states so that we can model the signal. You can learn more about it at https://www.robots.ox.ac.uk/~vgg/rg/slides/hmm.pdf. Before you proceed, you need to install the hmmlearn package. You can find the installation instructions at http://hmmlearn.readthedocs.org/en/latest. Let's take a look at how ...