code: def test_Speech2Text(
      use_lm, token_type, asr_config_file, lm_config_file
  ):
      speech2text = Speech2Text(
          asr_train_config=asr_config_file,
          lm_train_config=lm_config_file if use_lm else None,
          beam_size=1,
          token_type=token_type,
      )
      speech = np.random.randn(10000)
      hyps = speech2text(speech)
      results = speech2text.hypotheses_to_results(hyps)
  
      for text, token, token_int, hyp in results:
          assert text is None or isinstance(text, str)
          assert isinstance(token, List)
          assert isinstance(token_int, List)
          assert isinstance(hyp, Hypothesis)
  
imports: import string
  from argparse import ArgumentParser
  from distutils.version import LooseVersion
  from pathlib import Path
  from typing import List
  import numpy
  import pytest
  import torch
  from espnet2.asr_transducer.beam_search_transducer import Hypothesis
  from espnet2.bin.asr_transducer_inference import Speech2Text, get_parser, main
  from espnet2.tasks.asr_transducer import ASRTransducerTask
  from espnet2.tasks.lm import LMTask
label_desc: Use image node_id 8 for calling a global function with example usage: test_Speech2Text(use_lm, token_type, asr_config_file, lm_config_file) without return types