code: def extract_transcriptions(hyps):
      """
      The transcribed_texts returned by CTC and RNNT models are different.
      This method would extract and return the text section of the hypothesis.
      """
      if isinstance(hyps[0], Hypothesis):
          transcriptions = []
          for hyp in hyps:
              transcriptions.append(hyp.text)
      else:
          transcriptions = hyps
      return transcriptions
  
file_path: NeMo/examples/asr/asr_cache_aware_streaming/speech_to_text_cache_aware_streaming_infer.py
imports: import contextlib
  import json
  import os
  import time
  from argparse import ArgumentParser
  import torch
  from omegaconf import open_dict
  import nemo.collections.asr
  from nemo.collections.asr.metrics.wer import word_error_rate
  from nemo.collections.asr.parts.utils.rnnt_utils import Hypothesis
  from nemo.collections.asr.parts.utils.streaming_utils import CacheAwareStreamingAudioBuffer
  from nemo.utils import logging
label_desc: Use image node_id 1 for calling a global function with example usage: extract_transcriptions(hyps) and returns: transcriptions