Definitions for "Hidden Markov Model"
A Hidden Markov Model is a statistical model of the distribution of "hidden" features, such as phonemes or part-of-speech tags, based on observable features, such as acoustic segments, or words. The computational models can be automatically trained from data samples, and then used to recognize the "hidden" layer, based on the statistical model derived from the training data.
(HMM) An extension of a Markov model, in which a state has a probability of emitting some output; thus, states may be "hidden."
A numeric analysis technology used frequently in continuous-speech recognition systems that recognizes speech by determining the probability of each phoneme at contiguous, small regions (frames) of the speech signal item in a string of items.