In order to study the optimization method of Gaussian Mixture Model (GMM) based on variational inference in human voice recognition,the framework of human voice recognition system is first designed,and the basic principle and characteristics of traditional GMM in human voice recognition systems are described. Then,the basic principle of variational inference and its application in GMM optimization are introduced in detail. Finally,experimental evaluation is carried out with open data set.The simulation results show that the optimized GMM is significantly better than the traditional GMM in recognition accuracy,precision,recall,and F1 score.
关键词
高斯混合模型(GMM)/人声识别/变分推断/统计模型
Key words
Gaussian Mixture Model (GMM)/voice recognition/variational inference/statistical model
维普
万方数据