LSP Trajectory Analysis for Speech Recognition

Speech signal is the continuous signal which has the characteristics in its own. For recognizing the speech signal, the system must be able to classify and recognize the speech feature. Almost of this system is speaker-independent speech system. This paper presents statistical methods for speech recognition by extracting the features of the speech and analyzing their trajectory. The speech feature has been extracted to line spectral pairs (LSP) coefficients and then uses the statistic model to pattern the trajectory for recognizing the signal. The result shows that the using technique usually works well which the maximum accuracy of recognition is 99.67% at number 1 of male speech and the minimum accuracy of recognition is 82.33% at number 5 of female speech.