def METHOD_NAME(use_lm, token_type, slu_config_file, lm_config_file):
    speech2understand = Speech2Understand(
        slu_train_config=slu_config_file,
        lm_train_config=lm_config_file if use_lm else None,
        beam_size=1,
        token_type=token_type,
    )
    speech = np.random.randn(100000)
    results = speech2understand(speech)
    for text, token, token_int, hyp in results:
        assert text is None or isinstance(text, str)
        assert isinstance(token[0], str)
        assert isinstance(token_int[0], int)
        assert isinstance(hyp, Hypothesis)