A new algorithm for linear prediction coding based on neural network
Yong Wang · Journal of Zhejiang University of Technology · 2007
A new algorithm of linear prediction coding based on neural network is presented.In contrast with the prediction coefficients error of self-correlative method and instability of covariance method,this algorithm improves the short-time average precision observably.As the main content of multimedia information compressing technology,long-distance transmission of the speech parameter coding by narrow band signal channel plays an important role.Speech signal compressing is an important section of multimedia information compressing technology.The theory of LPC coding is researched based on the linear prediction coding technology,the least mean square rule is applied for improving the short-time average precision,and the self-correlative calculation of prediction coefficients are introduced.Finally the speech synthesizing experiment is carried out and the result demonstrates that it is not only proved to be an effective way that improves the precision but also ensures systemic stability.Up to 20 percent decrease of the mean square error of prediction coefficient by our method is obtained in contrasting with that of a traditional self-correlation method.When the original signal has a higher frequency,the quality of speech synthesizes with applying this algorithm would be more effective.