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What is HMMs in Speech Recognition Explained about?

The document discusses Hidden Markov Models (HMMs) and their application in speech recognition, highlighting key components such as states, observations, and probabilities. It explains the Viterbi algorithm, which is used to determine the most probable sequence of hidden states from a given observation sequence. An example is provided to illustrate the process of using the Viterbi algorithm to compute the most likely phoneme path.

Author

parthvasava62352

Language

EN