code: def calculate(file_list, gt_file_list, args, MCD):
      for i, cvt_path in enumerate(file_list):
          corresponding_list = list(
              filter(
                  lambda gt_path: get_basename(gt_path) in cvt_path,
                  gt_file_list,
              )
          )
          assert len(corresponding_list) == 1
          gt_path = corresponding_list[0]
          gt_basename = get_basename(gt_path)
  
          # extract ground truth and converted features
          gt_feats = world_extract(gt_path, args)
          cvt_feats = world_extract(cvt_path, args)
  
          # VAD & DTW based on power
          gt_mcep_nonsil_pow = extfrm(
              gt_feats["mcep"], gt_feats["npow"]
          )
          cvt_mcep_nonsil_pow = extfrm(
              cvt_feats["mcep"], cvt_feats["npow"]
          )
          _, path = fastdtw(
              cvt_mcep_nonsil_pow,
              gt_mcep_nonsil_pow,
              dist=scipy.spatial.distance.euclidean,
          )
          twf_pow = np.array(path).T
  
          # MCD using power-based DTW
          cvt_mcep_dtw_pow = cvt_mcep_nonsil_pow[twf_pow[0]]
          gt_mcep_dtw_pow = gt_mcep_nonsil_pow[twf_pow[1]]
          diff2sum = np.sum(
              (cvt_mcep_dtw_pow - gt_mcep_dtw_pow) ** 2, 1
          )
          mcd = np.mean(10.0 / np.log(10.0) * np.sqrt(2 * diff2sum), 0)
  
          print("{} {}".format(gt_basename, mcd))
          MCD.append(mcd)
  
imports: import argparse
  import fnmatch
  import multiprocessing
  import os
  import numpy
  import pysptk
  import pyworld
  import scipy
  from fastdtw import fastdtw
  from scipy.io import wavfile
  from scipy.signal import firwin, lfilter
label_desc: Use image node_id 8 for calling a global function with example usage: calculate(file_list, gt_file_list, args, MCD) without return types