code: def test_inference_ctc_normal(self):
      model = MCTCTForCTC.from_pretrained("speechbrain/m-ctc-t-large")
      model.to(torch_device)
      processor = MCTCTProcessor.from_pretrained(
          "speechbrain/m-ctc-t-large", do_lower_case=True
      )
      input_speech = self._load_datasamples(1)
  
      input_features = processor(
          input_speech, return_tensors="pt"
      ).input_features.to(torch_device)
  
      with torch.no_grad():
          logits = model(input_features).logits
  
      predicted_ids = torch.argmax(logits, dim=-1)
      predicted_trans = processor.batch_decode(predicted_ids)
  
      EXPECTED_TRANSCRIPTIONS = [
          "a man said to the universe, sir, i exist."
      ]
      self.assertListEqual(predicted_trans, EXPECTED_TRANSCRIPTIONS)
  
imports: import inspect
  import math
  import unittest
  from datasets import load_dataset
  from transformers import MCTCTConfig, is_torch_available
  from transformers.testing_utils import require_soundfile, require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor
label_desc: Use image node_id 2 for calling the MCTCTModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_ctc_normal() without return types