For example, if we have a dataset that has values between 0 and 5,000, after mean normalization the range of values will be distributed in some small range around 0, for example between -3 to 3.

Z-score normalization converts data values to standard deviations from the mean, while Min-max normalization rescales the data values to a range between zero and one.

Choose a normalization method, which can be min-max scaling to rescale to 0-1 range or z-score standardization to center the mean around 0 with a standard deviation of 1.

Cepstral Mean and Variance Normalization (CMVN) is a computationally efficient normalization technique for noise robust speech recognition. The performance of CMVN is known to degrade for short ...

This paper presents the effect of mean normalization to various types of cepstral coefficients for robust speech recognition in noisy environments. Although the cepstral mean normalization (CMN) ...