An Optimized Design of VQ Codebook Based on Genetic Algorithm
Vector Quantization is one of popular codebook design methods for speaker recognition at present. In the process of codebook design, traditional LBG algorithm owns the advantage of fast convergence, but it is easy to get the local optimal result and be influenced by initial codebook. According to the understanding that Genetic Algorithm has the capability of getting the global optimal result, this paper proposes a hybrid clustering method GA-L based on Genetic Algorithm and LBG algorithm to improve the codebook. Concrete complementation of the GA-L method as well as the experiments is given. The experiment shows the proposed GA-L method is effective and improved the performance of traditional LBG algorithm. This method can not only distill the individual information, in favor of speakers model, but also improve the recognition performance.
speaker recognition GA-L vector quantization Genetic Algorithm
GAO liai ZHANG Shuguang CHENG Man YUAN Hongbo ZhAO Xueliang JIANG Bingliang
College of Mechanical and Electrical Engineering, Agriculture University of Hebei, Baoding 071001
国际会议
北京
英文
2007-08-05（万方平台首次上网日期，不代表论文的发表时间）