Design of Modular Scalable HMM-based Continuous Speech Recognition / Convolutional Decoder IP

Abstract

This paper presented a design method of modular scalable HMM-based continuous speech recognition / convolutional decoder IP. This IP includes three major functions: (i) Hidden Markov Model based continuous speech recognition (ii) convolutional decoder of error control coding (iii) modular scalable IP design. Since the recognition kernel of HMM-based speech recognition system and the decoding kernel of convolutional coding system are similar, we integrate the two functions in one IP by working with same hardware modules. Besides, in order to satisfy the number of recognizable words requirement of most speech recognition applications, we develop the modular scalable IP architecture that one can increase the number of recognizable words by cascoding connection with speech recognition IPs and extension modules.