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1.3 HMM Tagging Problem: Viterbi Algorithm Tag the following input: station control ground Once again we have assumed an end of sentence marker A, which
1.3 HMM Tagging Problem: Viterbi Algorithm Tag the following input: station control ground Once again we have assumed an end of sentence marker A, which according to our model, only ever occurs with the tag End. This can be done by computing the products of the transition probabilities (called the path probabilities) for all 16 paths through the HMM and choosing the most probable path. But the assigned problem is to choose the most probable path by using the Viterbi algorithm. You will hand in the completed Viterbi matrix and the calculations you used to fill it, and the tag sequence that the algorithm identifies as the most probable To help you get started, here is the partial Viterbi matrix for our HMM and the given input 1.3 HMM Tagging Problem: Viterbi Algorithm Tag the following input: station control ground Once again we have assumed an end of sentence marker A, which according to our model, only ever occurs with the tag End. This can be done by computing the products of the transition probabilities (called the path probabilities) for all 16 paths through the HMM and choosing the most probable path. But the assigned problem is to choose the most probable path by using the Viterbi algorithm. You will hand in the completed Viterbi matrix and the calculations you used to fill it, and the tag sequence that the algorithm identifies as the most probable To help you get started, here is the partial Viterbi matrix for our HMM and the given input
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