摘要
说话人识别的方法很多 ,提出的基于矢量量化 (VQ)的算法 ,在语音特征表征上利用几种特征参数的组合使用来提高识别率 ,在VQ过程中 ,经典的K均值算法收敛速度快 ,但极易收敛于局部最佳点 ,为了使聚类算法收敛于全局最优点 ,同时提高识别率 ,采用模拟退火算法来改善聚类码本质量 .讨论了具体的算法实现 ,并给出了一些实验数据 ,实验结果表明该处理方法是有效的 .
A speaker recognition algorithm based on vector quantization is presented.In order to obtain better recognition rate,some different characteristic parameters are adapt that can be mixed into a specific vector.In the process of VQ,traditional K-means algorithm owns the advantage of fast convergence,but it is difficult to get the global optimal result.To solve this problem,annealing algorithm is applied to improving the clusters' quality.The details of the algorithm and related experiments are given.The results demonstrate this approach is effective.
出处
《云南大学学报（自然科学版）》
CAS
CSCD
2002年第2期96-100,共5页
Journal of Yunnan University(Natural Sciences Edition)
基金
云南省自然科学基金资助项目 ( 99F0 0 16M )
