14 ms / frame -0.6 sec 1000We have developed speech recognition middleware on a RISC microprocessor which has robust processing functions against environmental noise and speaker ditkences. The speech recognition middleware enables developers and users to use a speech recognition process fbr m n y possible speech applications, such as car navigation system and handheld PCs. In this paper, we report implemntation issues ofspeech recognition process in middleware of microprocessors and propose robust noise handling hnctions using ANC(Adaptive Noise Cancellation) and noise adapt\ve models. We also propose a new speaker adaptation algorithm, in which the relationships among HMMs(Hidden Markov Models) transkr vectors are provided as a set of pre-trained interpolation coefficients. Experimental evaluations on 1000-word vocabulary speech recognition showed promising results h r both robust processing functions ofthe proposed noise handling methods and the proposed speaker adaptation method.
SUMMARYA method for handling noise in a car information machine incorporating speech recognition middleware and having a SuperH (SH) Micon as its platform is reported. Using both a noise acoustic model and a spectral subtraction scheme, this method is evaluated by computer simulation against an evaluation database constructed by considering the usage environment and the microphone position. In evaluations using the noise model alone, a speech recognition rate of 11.0% in a test track driving environment was obtained when an HMM tutored by speech without noise was used, while a recognition rate of 82.7% was obtained when an HMM constructed by superimposing noise over the tutoring speech was used. The speech recognition rate was improved by about an additional 5%, to 87.6%, by using this noise-containing acoustic model and the spectral subtraction scheme. In addition, when speech recognition middleware incorporated with the antinoise method was loaded on an SH board, a recognition performance comparable with the computer simulation results was obtained.
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