postprocessing

Global Cepstral Mean and Variance Normalization

speechpy.processing.cmvn(vec, variance_normalization=False)[source]

This function is aimed to perform global cepstral mean and variance normalization (CMVN) on input feature vector “vec”. The code assumes that there is one observation per row.

Parameters:
  • vec (array) – input feature matrix (size:(num_observation,num_features))
  • variance_normalization (bool) – If the variance normilization should be performed or not.
Returns:

The mean(or mean+variance) normalized feature vector.

Return type:

array

Local Cepstral Mean and Variance Normalization over Sliding Window

speechpy.processing.cmvnw(vec, win_size=301, variance_normalization=False)[source]

This function is aimed to perform local cepstral mean and variance normalization on a sliding window. (CMVN) on input feature vector “vec”. The code assumes that there is one observation per row.

Parameters:
  • vec (array) – input feature matrix (size:(num_observation,num_features))
  • win_size (int) – The size of sliding window for local normalization. Default=301 which is around 3s if 100 Hz rate is considered(== 10ms frame stide)
  • variance_normalization (bool) – If the variance normilization should be performed or not.
Returns:

The mean(or mean+variance) normalized feature vector.

Return type:

array