Abstract
The speech signals were analyzed by means of short-time Fourier transform,and the time series clusters that were composed of the same frequency's energy series of each speech were gained.Between every column vector serie and the serie consisting of every row vector's average value,the linear regression equations were established based on time series pretreatment and mathematical statistics.The deterministic parts and stochastic parts of the time series cluster were separated,and the feature parameters were extracted from speech signals of the speaker,then the speech signals were recognized.The experimental results show that the highest average recognition rate is 97.94%,with the distance parameter described in this paper and three frequencies on the speech set of 194 speech signals pronounced by eight speakers.
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