Speaker recognition method based on speech feature fusion and GMMs

The invention relates to a speaker recognition method based on speech feature fusion and GMMs (Gaussian Mixture Models). According to the method, first, different types of speech feature parameters are fused to acquire new speech feature parameters, and the new feature parameters are used for training of a recognition model; and in the establishing process of the recognition model, the two GMMs are connected in series through a threshold function, so that the recognition model is optimized. Through the method, the new speech feature parameters are extracted and have respective advantages of multiple types of speech feature parameters, and personalized features of a speaker can be better represented; and moreover, the two GMMs are connected in series through the threshold function for recognition, so that the accuracy of speaker recognition is improved compared with a single GMM. 本发明涉及一种一种基于语音特征融合和GMM的说话人识别方法。本发明首先通过融合不同类型语音特征参数从而获取的新的语音特征参数，并将新的特征参数用于识别模型的训练，并且在识别模型建立过程中，通过阈值函数将两个高斯混合模型进行串联，优化了识别模型。本发明提取新的语音特