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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users.
* More info + downloads: https://mlpack.org
* Git repo: https://github.com/mlpack/mlpack
The General HiddenMarkov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of HiddenMarkov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
This project (CvHMM) is an implementation of discrete HiddenMarkov Models (HMM) based on OpenCV. It is simple to understand and simple to use. The Zip file contains one header for the implementation and one main.cpp file for a demonstration of how it works. Hope it becomes useful for your projects.
HMMLab is a HiddenMarkov Model editor oriented on HMMs for speach recognition. It can create, edit, train and visualize HMMs. HMMLab supports loading/saving HMMs from/to HTK files.