Development of robust speech recognition middleware on microprocessor

We have developed speech recognition middleware on a RISC microprocessor which has robust processing functions against environmental noise and speaker differences. The speech recognition middleware enables developers and users to use a speech recognition process for many possible speech applications, such as car navigation systems and handheld PCs. We report implementation issues of speech recognition process in middleware of microprocessors and propose robust noise handling functions using ANC (adaptive noise cancellation) and noise adaptive models. We also propose a new speaker adaptation algorithm in which the relationships among HMMs (hidden Markov models) transfer vectors are provided as a set of pre-trained interpolation coefficients. Experimental evaluations on 1000-word vocabulary speech recognition showed promising results for both robust processing functions of the proposed noise handling methods and the proposed speaker adaptation method