code: def spectral_skewness(signal, fs):
      """Measures the asymmetry of a distribution around its mean value.
  
      Description and formula in Article:
      The Timbre Toolbox: Extracting audio descriptors from musicalsignals
      Authors Peeters G., Giordano B., Misdariis P., McAdams S.
  
      Feature computational cost: 2
  
      Parameters
      ----------
      signal : nd-array
          Signal from which spectral skewness is computed
      fs : float
          Sampling frequency
  
      Returns
      -------
      float
          Spectral Skewness
  
      """
      f, fmag = calc_fft(signal, fs)
      spect_centr = spectral_centroid(signal, fs)
  
      if not spectral_spread(signal, fs):
          return 0
      else:
          skew = ((f - spect_centr) ** 3) * (fmag / np.sum(fmag))
          return np.sum(skew) / (spectral_spread(signal, fs) ** 3)
  
imports: import scipy.signal
  from tsfel.feature_extraction.features_utils import *
label_desc: Use image node_id 44 for calling a global function with example usage: spectral_skewness(signal, fs) and returns: int, unknown