MFCC feature weighting MFCC特征加权
This feature vector made the Gaussian Mixture Model (GMM) classifier outperform MFCC and Differential MFCC features in classification.
该混合特征使得高斯混合模型(GMM)分类器可获得比使用MFCC特征及其差分MFCC更好的分类性能。
During the experiment, MFCC (Mel Frequency Ceptral Coefficient) is adopted to speaker speech feature parameters.
实验中，采用美尔倒谱系数(MFCC)作为话者语音特征参数。
The experiment results indicate that the new feature parameter WPP is able to outperform SBC and SBC is better than MFCC.
实验证明新特征参数WPP的语音识别性能优于SBC，而SBC的识别性能优于MFCC。
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