A micropower analog circuit implementation of hidden Markov model state decoding

We describe the implementation of a hidden Markov model state decoding system, a component for a wordspotting speech recognition system. The key specification for this state decoder design is microwatt power dissipation: this requirement led to a continuous-time, analog circuit implementation. We describe the tradeoffs inherent in the choice of an analog design and explain the mapping of the discrete-time state decoding algorithm into the continuous domain. We characterize the operation of a ten-word (81-state) state decoder test chip.