(feats, mean, variance, epsilon=1e-9)
return (feats - mean) * tf.rsqrt(variance + epsilon)
TF: apply CMVN on feature
TF: apply CMVN on feature
TF : apply CMVN on feature
def apply_cmvn(feats, mean, variance, epsilon=1e-9):
  ''' TF: apply CMVN on feature'''
  return (feats - mean) * tf.rsqrt(variance + epsilon)
def apply_cmvn ( feats , mean , variance , epsilon = 1e-9 ) : return ( feats - mean ) * tf . rsqrt ( variance + epsilon )