Hardware Implementation of Probabilistic State Machine for Word Recognition

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Provided by: International Journal on Electronics & Communication Technology (IJECT)
Topic: Hardware
Format: PDF
Probabilistic Finite State Machines (PFSM) are used in feature extraction, training and testing which are the most important steps in any speech recognition system. An important PFSM is the hidden Markov model which is dealt in this paper. This paper proposes a hardware architecture for the forward-backward algorithm as well as the Viterbi algorithm used in speech recognition based on hidden Markov models. The feature extraction and the training process is done using Hidden markov model (HTK) Tool Kit.
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