code: def get_subset_of_audio_manifest(
      audio_manifest: dict,
      offset_index: int,
      max_audio_read_sec: float,
      min_alignment_count: int,
  ) -> dict:
      """
      Get a subset of `audio_manifest` for faster audio-file reading.
  
      Args:
          audio_manifest (dict): Audio manifest dictionary.
              keys: 'offset', 'duration', 'alignments', 'words'
          offset_index (int): Index of the offset.
          max_audio_read_sec (float): Maximum audio read duration.
          min_alignment_count (int): Minimum number of alignments to read.
  
      Returns:
          audio_manifest (dict): Subset of `audio_manifest` is returned for `words` and `alignments` keys.
      """
      alignment_array = np.array(audio_manifest["alignments"])
      alignment_array_pr = (
          np.array(alignment_array[offset_index:])
          - alignment_array[offset_index]
      )
      subset_alignments = alignment_array_pr[
          alignment_array_pr < max_audio_read_sec
      ]
      if len(subset_alignments) < min_alignment_count:
          # Cases where the word next to the offset is longer than the max_audio_read_sec.
          logging.warning(
              f"subset_alignments of {audio_manifest['audio_filepath']} \n"
              f"has subset alignment length:{len(subset_alignments)} at offset_index:{offset_index}, "
              f"word:{audio_manifest['words'][offset_index:offset_index+min_alignment_count]}, "
              f"alignments:{alignment_array_pr[:min_alignment_count]} which is longer than _max_audio_read_sec:{[0, max_audio_read_sec]}."
              " Truncating the alignements."
          )
          # Attach the `_max_audio_read_sec` to the `subset_alignments` to truncate the alignment timestamp.
          subset_alignments = np.concatenate(
              [subset_alignments, np.array([max_audio_read_sec])]
          )
      audio_manifest["offset"], audio_manifest["duration"] = (
          alignment_array[offset_index],
          subset_alignments[-1] - subset_alignments[0],
      )
      audio_manifest["alignments"] = subset_alignments.tolist()
      audio_manifest["words"] = audio_manifest["words"][
          offset_index : offset_index + len(subset_alignments)
      ]
      return audio_manifest
  
imports: import copy
  import os
  import shutil
  from collections import defaultdict
  from typing import IO, Dict, List, Optional, Tuple
  import numpy
  import torch
  from scipy.stats import beta, gamma
  from tqdm import tqdm
  from nemo.collections.asr.parts.preprocessing.perturb import AudioAugmentor
  from nemo.collections.asr.parts.preprocessing.segment import AudioSegment
  from nemo.collections.asr.parts.utils.manifest_utils import get_ctm_line, read_manifest, write_ctm, write_manifest, write_text
  from nemo.collections.asr.parts.utils.speaker_utils import labels_to_rttmfile
  from nemo.utils import logging
label_desc: Use image node_id 3 for calling a global function with example usage: get_subset_of_audio_manifest(audio_manifest, offset_index, max_audio_read_sec, min_alignment_count) and returns: audio_manifest