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A speech recognizer with selectable model parameters

This paper presents the design and simulation results of a hidden Markov model (HMM) based isolated word recognizer IC. The new design can handle any combination of states and mixtures (up to 16 states and 8 mixtures). The speech IC has been verified with 353 test speech data. The recognition accuracy is 93.8% (48-bit) with no truncation and 88.9% with truncation (16-bit).