code: def extract_fbank(
      samples, sr=8000, winlen=0.025, winstep=0.01, feature_size=40
  ):
      """extract logfbank with delta and delta-delta
      Return:
          ndarray of shape [nfrmae, feature_size * 3]
      """
      feat = psf.logfbank(
          samples,
          nfilt=feature_size,
          samplerate=sr,
          winlen=winlen,
          winstep=winstep,
          lowfreq=0,
          highfreq=None,
          preemph=0.97,
      )
      delta = psf.delta(feat, N=2)
      _delta_delta = psf.delta(delta, N=2)
      return np.stack([feat, delta, _delta_delta], axis=-1)
  
file_path: delta/delta/data/feat/speech_feature.py
imports: import os
  import numpy
  import delta.compat
  from absl import logging
  from delta.data.feat import speech_ops
  from core.ops import py_x_ops
  from delta.data.feat import python_speech_features
label_desc: Use image node_id 7 for calling a global function with example usage: extract_fbank(samples, sr, winlen, winstep, feature_size) and returns: np