code: def test_predict(self, art_warning):
      try:
          transcripts = list()
          audios = list()
          for filename, sample in self.samples.items():
              file_path = get_file(filename, sample["uri"])
              _, audio = read(file_path)
              audios.append(audio)
              transcripts.append(sample["transcript"])
  
          audio_batch = np.array(audios, dtype=object)
  
          lingvo = TensorFlowLingvoASR()
          prediction = lingvo.predict(audio_batch, batch_size=1)
          assert prediction[0] == transcripts[0]
      except ARTTestException as e:
          art_warning(e)
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_equal
  from scipy.io.wavfile import read
  from art.estimators.speech_recognition.speech_recognizer import SpeechRecognizerMixin
  from art.estimators.speech_recognition.tensorflow_lingvo import TensorFlowLingvoASR
  from art.estimators.tensorflow import TensorFlowV2Estimator
  from art.utils import get_file
  from tests.utils import ARTTestException
label_desc: Use image node_id 1 for calling the TestTensorFlowLingvoASRLibriSpeechSamples obj's underlying member method code with example usage: obj.test_predict(art_warning) without return types