This thesis established the DSP-based and PC-based system for speech keyword retrieval and recognition according to the same basic algorithm. This system does not need to train speech models, and the keywords and describing sentences do not put the limit of the number of words and could be any language. Before calculating the speech features, the speech signal need to be pre-processed. The pre-process includes DC bias removing, segment, Rabiner & Sambur end point detection, pre-emphasis, and windowing. About the speech features, the system used 12 degrees of Mel-Frequency cepstral coefficient and 12 degrees of delta coefficient to make a 24-degreed speech feature. The key point of the system is the process of pattern comparison. The system adopted dynamic time warping cooperating with one pass algorithm to improve the optimal process. In order to attain the DSP system, using an optimum likelihood ratio threshold to be the determine standard for not keyword rejection. All of the keywords use the same threshold in the method. It improves the original method which uses least differential to set up the threshold by reducing the requirement of ram. After testing in the experiments, the speech keyword retrieval and recognition system both have great recognition and efficiency.

In this thesis, the PC base and DSP base speech keyword retrieval and recognition systems could work. The keywords and describing sentences will not have the limit of word length and could be any languages. Besides, training speech models is not needed anymore. It means that the database gets its expansibility without training speech models again. We can establish the system on the PC base, and calculate the program with fixed-point DSP board. In the processing of speech signal, lots of mathematical functions will be required. We must reach its immediately effect, so that the system could be useful. In addition, compared with floating point, the fixed point DSP cost much less; it makes the system nearer to users. After being tested by experiments, the speech keyword retrieval and recognition system got great recognition and efficiency.