code: def test_Speech2Understand(slu_config_file):
      speech2understand = Speech2Understand(
          slu_train_config=slu_config_file, beam_size=1
      )
      speech = np.random.randn(1000)
      results = speech2understand(speech)
      for text, token, token_int, hyp in results:
          assert isinstance(text, str)
          assert isinstance(token[0], str)
          assert isinstance(token_int[0], int)
          assert isinstance(hyp, Hypothesis)
  
file_path: espnet/test/espnet2/bin/test_slu_inference.py
imports: import string
  from argparse import ArgumentParser
  from distutils.version import LooseVersion
  from pathlib import Path
  import numpy
  import pytest
  import torch
  from espnet2.bin.slu_inference import Speech2Understand, get_parser, main
  from espnet2.tasks.lm import LMTask
  from espnet2.tasks.slu import SLUTask
  from espnet.nets.beam_search import Hypothesis
label_desc: Use image node_id 5 for calling a global function with example usage: test_Speech2Understand(slu_config_file) without return types