A study on the improvement of speaker recognition system by voiced detection

The effect of silence segment elimination on the improvement of a speaker recognition system was investigated in this study. The speaker recognition system is a method to identify input speech of a speaker by the comparison of previously registered and the test speech. The performance of this system greatly depends on a preprocessing stage. The experiments on the extraction of speech segments from speech wave forms during the preprocessing stage were conducted to analyze the rate of recognition. A new measure was developed and proposed, based on the fact that the slope of a valley at the pitch point in speech wave forms is higher when the normalized AMDF was applied to the stationary and transition regions. Voiced segments were extracted from the speech wave forms. From the voice segments, unvoiced segments were then detected using the autocorrelation ratio for the adjacent samples at the front and rear regions of the voiced segments. The results of this study indicated that this proposed method increased the perception rate by approximately 2% but had little effect on recognition time.