منابع مشابه
Adjusted Viterbi Training
We propose modifications of the Viterbi Training (VT) algorithm to estimate emission parameters in Hidden Markov Models (HMM) which are widely used in speech recognition, natural language modeling, image analysis, and bioinformatics. Our goal is to alleviate the inconsistency of VT while controlling the amount of extra computations. Specifically, we modify VT to enable it asymptotically to fix ...
متن کاملAdjusted Viterbi training for hidden Markov models
We consider estimation of the emission parameters in hidden Markov models. Commonly, one uses the EM algorithm for this purpose. However, our primary motivation is the Philips speech recognition system wherein the EM algorithm is replaced by the Viterbi training algorithm. Viterbi training is faster and computationally less involved than EM, but it is also biased and need not even be consistent...
متن کاملAdjusted Viterbi Training. A proof of concept
Viterbi Training (VT) provides a fast but inconsistent estimator of Hidden Markov Models (HMM). The inconsistency is alleviated with little extra computation when we enable VT to asymptotically fix the true values of the parameters. This relies on infinite Viterbi alignments and associated with them limiting probability distributions. First in a sequel, this paper is a proof of concept; it focu...
متن کاملThe adjusted Viterbi training for hidden Markov models
The EM procedure is a principal tool for parameter estimation in the hidden Markov models. However, applications replace EM by Viterbi extraction, or training (VT). VT is computationally less intensive, more stable and has more of an intuitive appeal, but VT estimation is biased and does not satisfy the following fixed point property. Hypothetically, given an infinitely large sample and initial...
متن کاملViterbi training in PRISM
VT (Viterbi training), or hard EM, is an efficient way of parameter learning for probabilistic models with hidden variables. Given an observation y , it searches for a state of hidden variables x that maximizes p(x , y | θ) by coordinate ascent on parameters θ and x . In this paper we introduce VT to PRISM, a logic-based probabilistic modeling system for generative models. VT improves PRISM in ...
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ژورنال
عنوان ژورنال: Probability in the Engineering and Informational Sciences
سال: 2007
ISSN: 0269-9648,1469-8951
DOI: 10.1017/s0269964807000083