code: def test_transcription(self, speech_regression_model, test_data_dir):
      audio_filenames = ["an22-flrp-b.wav", "an90-fbbh-b.wav"]
      audio_paths = [
          os.path.join(test_data_dir, "asr", "train", "an4", "wav", fp)
          for fp in audio_filenames
      ]
  
      model = speech_regression_model.eval()
  
      # Test Top 1 classification transcription
      results = model.transcribe(audio_paths, batch_size=2)
      assert len(results) == 2
  
imports: import os
  import pytest
  from omegaconf import DictConfig
  from nemo.collections.asr.models.classification_models import EncDecRegressionModel
label_desc: Use image node_id 2 for calling the TestEncDecRegressionModel obj's underlying member method code with example usage: obj.test_transcription(speech_regression_model, test_data_dir) without return types