Compute Spectral Subband Centroid features from an audio signal.
An array of size (NUMFRAMES by nfilt) containing features. Each row holds 1 feature vector.
the audio signal from which to compute features. Should be an N*1 array
the sample rate of the signal we are working with, in Hz.
the length of the analysis window in seconds. Default is 0.025s (25 milliseconds)
the step between successive windows in seconds. Default is 0.01s (10 milliseconds)
the number of filters in the filterbank, default 26.
the FFT size. Default is 512.
lowest band edge of mel filters. In Hz, default is 0.
highest band edge of mel filters. In Hz, default is samplerate/2
apply preemphasis filter with preemph as coefficient. 0 is no filter. Default is 0.97.
the analysis window to apply to each frame. By default no window is applied. You can use numpy window functions here e.g. winfunc=numpy.hamming