A novel speaker adaptation algorithm and its implementation on a RISC microprocessor

We have developed speech recognition middleware on a RISC microprocessor. The speech recognition function is required in many applications of RISC microprocessors, such as ear navigation systems and handheld PCs. The speech recognition middleware provides a fundamental library for developers to make those applications. Speaker adaptation is one of the most important functions to realize robust recognition performance. As part of the speech recognition middleware, we have developed a new speaker adaptation algorithm, in which the relationships among HMM (hidden Markov model) transfer vectors are provided as a set of pre-trained interpolation coefficients. Experimental evaluations showed promising results that 28% of recognition errors are reduced using 10 words for adaptation and 52% are reduced using 50 words.