code: def filter_audio_paths(
      path: str,
      language: str,
      lst_name: str,
  ):
      """Extract audio paths for the given language."""
      audio_paths = []
  
      path = Path(path)
      with open(path / "scoring" / lst_name) as f:
          for line in f:
              audio_path, lang = line.strip().split()
              if language is not None and lang != language:
                  continue
              audio_path = re.sub(r"^.*?\/", "", audio_path)
              audio_paths.append(path / audio_path)
  
      return audio_paths
  
file_path: audio/src/torchaudio/datasets/quesst14.py
imports: import os
  import re
  from pathlib import Path
  from typing import Optional, Tuple, Union
  import torch
  from torch.utils.data import Dataset
  from torchaudio._internal import download_url_to_file
  from torchaudio.datasets.utils import _extract_tar, _load_waveform
label_desc: Use image node_id 1 for calling a global function with example usage: filter_audio_paths(path, language, lst_name) and returns: audio_paths