A generic code for sequential conditional random fields

I have made available the C++ code for sequential labelling tasks such as part-of-speech tagging, noun-phrase chunking or human activity annotation. The code is domain independent and supports the following features:

• First & second-order sequential CRFs.
• Training algorithms: L-BFGS (from Taku Kudo), stochastic gradient ascent and Collin's voted perceptron.
• Handle missing training labels.
• Decoding: Viterbi (forward/backward) and Pearl's max-product.
• Report label-wise and segment-wise statistics.

The project page is here. The page contains a tutorial on the theory of CRFs and a discussion on the implementation.