| 摘要 |
A stand-alone, real-time voice recognition system, which converts an analog voice signal into serial digital signal, then preprocesses in parallel the digital signal to detect the end-point, and output fixed multi-order prediction coefficients. In this recognition system, these multi-order prediction coefficients are stored as the reference pattern in the training mode. In recognition mode, these multi-order prediction coefficients are adapted by dynamic time warping method, which is modified by a symmetric form. This symmetric form is implemented with a one-dimensional circular buffer for dynamic programming matching instead of the traditional two-dimensional buffer to save memory space. Finally, these adapted coefficients are compared with reference pattern to output the result of recognition.
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