old_contents: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  
  from itertools import product
  
  from librosa import load
  from pyvad import trim
  
  fs_vads = (8000, 16000, 32000, 48000)
  hops = (10, 20, 30)
  vad_modes = (0, 1, 2, 3)
  
  name = "voice/arctic_a0007.wav"
  data, fs = load(name, sr=None)
  
  for fs_vad, hop, vad_mode in product(fs_vads, hops, vad_modes):
      vact = trim(data, fs, fs_vad=16000, hoplength=30, vad_mode=0)
  
  name = "noise.wav"
  data, fs = load(name, sr=None)
  
  for fs_vad, hop, vad_mode in product(fs_vads, hops, vad_modes):
      vact = trim(data, fs, fs_vad=16000, hoplength=30, vad_mode=0)
  
new_contents: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  
  from itertools import product
  
  import numpy as np
  from librosa import load
  from pyvad import trim
  
  fs_vads = (8000, 16000, 32000, 48000)
  hops = (10, 20, 30)
  vad_modes = (0, 1, 2, 3)
  
  name = "voice/arctic_a0007.wav"
  data, fs = load(name, sr=None)
  
  for fs_vad, hop, vad_mode in product(fs_vads, hops, vad_modes):
      vact = trim(data, fs, fs_vad=16000, hoplength=30, vad_mode=0)
  
  fs = 16000
  data = (np.random.rand(fs*3)-0.5)*0.1
  
  for fs_vad, hop, vad_mode in product(fs_vads, hops, vad_modes):
      vact = trim(data, fs, fs_vad=16000, hoplength=30, vad_mode=0)
  
subject: fix noise of trim_test.py