Markov Modeling Package
This software includes basic implementations of the mixed membership Markov model (M4), introduced and described in the paper below, as well as a block HMM implementation. See the included README for open licensing information as well as usage instructions and input/output formatting guidelines.
M4 and the block HMM are used to model sequences of text blocks, such as paragraphs in an article or messages in a conversation. In the same way that topic models can discover unsupervised clusters of semantically related words, these Markov models can discover word clusters which also respect sequential context. When applied to conversation data, these have been shown to discover word classes resembling speech/dialog acts.
Please contact me if you find any bugs/errors. It may be a good idea to check back every once in a while in case there are future updates, especially in case bugs are discovered.