code: def test_using_audio_utils(self):
      # Tests that it uses audio_utils instead of torchaudio
      feat_extract = self.feature_extraction_class(
          **self.feat_extract_tester.prepare_feat_extract_dict()
      )
  
      self.assertTrue(hasattr(feat_extract, "window"))
      self.assertTrue(hasattr(feat_extract, "mel_filters"))
  
      from transformers.models.audio_spectrogram_transformer.feature_extraction_audio_spectrogram_transformer import (
          is_speech_available,
      )
  
      self.assertFalse(is_speech_available())
  
imports: import itertools
  import os
  import random
  import tempfile
  import unittest
  import numpy
  from transformers import ASTFeatureExtractor
  from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
  from transformers.utils.import_utils import is_torch_available
  from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
label_desc: Use image node_id 1 for calling the ASTFeatureExtractionWithoutTorchaudioTest obj's underlying member method code with example usage: obj.test_using_audio_utils() without return types