code: import numpy
  import librosa
  import glob
  import os
  import shutil
  
  full_clips = glob.glob("Full_Clips/*.mp3")
  print("Number of full clips: " + str(len(full_clips)))
  
  for clip in full_clips:
      clip_name = clip[11:]
      print("Current clip: " + clip_name)
      signal, fs = librosa.load(clip)
      signal_abs = numpy.absolute(signal)
  
      search_name = "Cut_Clips/" + clip_name[:-4] + "*[0-9].*"
      cut_clips = glob.glob(search_name)
      print("Number of clip segments: " + str(len(cut_clips)))
  
      total_mean = numpy.mean(signal_abs)
      print("Signal Total mean: " + str(total_mean))
      condition = total_mean*0.25
  
      for record in cut_clips:
          signal_segment, sample_rate_segment = librosa.load(record)
          mean = numpy.mean(numpy.abs(signal_segment))
          if mean < condition:
              print(record)
              print("Segment mean: " + str(mean))
              shutil.move(record,"Rejected_noise/")    
                  
  rejected_clips = glob.glob("Rejected_noise/*.wav")
  print(rejected_clips)
  for item in rejected_clips:
      name = item[15:]
      new_name = "All_MFCCs/" + name[:-3] + "png"
      if os.path.isfile(new_name):
          shutil.move(new_name, "Rejected_MFCCS/")        
  
apis: numpy.mean numpy.abs numpy.absolute