postprocessing¶
Processing module for signal processing operations.
This module demonstrates documentation for the signal processing function which are required as internal computations in the package.
ivar preemphasis:  

Preemphasising on the signal. This is a preprocessing step.  
ivar stack_frames:  
Create stacking frames from the raw signal.  
ivar fft_spectrum:  
Calculation of the Fast Fourier Transform.  
ivar power_spectrum:  
Power Spectrum calculation.  
ivar log_power_spectrum:  
Log Power Spectrum calculation.  
ivar derivative_extraction:  
Calculation of the derivative of the extracted featurs.  
ivar cmvn:  Cepstral mean variance normalization. This is a post processing operation. 
ivar cmvnw:  Cepstral mean variance normalization over the sliding window. This is a post processing operation. 
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. 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