A Fast Algorithm for Discrete Hmmtraining Using Observed Transitions
نویسنده
چکیده
We present a new algorithm to estimate the parameters of a Hidden Markov Model (HMM), specifically the transition probability matrix of the hidden states and the emission probabilities, given an observed sequence of data. The algorithm uses the number of transitions present in the observed label sequence and computes the parameters in an iterative fashion. We present experiments that demonstrate significant speed gains obtained by the current algorithm as compared to traditional algorithms such as Baum-Welch iterations.
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تاریخ انتشار 2010