改进的繁殖码激励线性预测编码器

Improved populating code-excted linear predictive coder

尽管码激励线性预测编码（ＣＥＬＰ）算法在中、低比特速率中已提供了较好的语音质量，但对随机码本的全搜索，其计算是极其复杂的。本文在繁殖码激励线性预测编码器的基础上研究了决定最优激励的全搜索过程，提出了用改进的繁殖码本作为激励源的有效搜索方法，使ＣＥＬＰ编码器的计算量减少为正常全搜索的。

Although CELP(code-excited linear predictive)coding has provided good quality synthetic speech at medium and low bit raes , the computation of an exhaustive search for stochastic codebook is extremely complex. This paper on the basis of populating code-excited linear predictive coder studies the exhaustive search procedure for deter-mining the optimum excitation,and develops an effective search methed by using im-proved populating codebook as excitation source. The computational cost of CELP coder was reduced to 1/26 that of a conventional full-gaussian codebook search.