code: def speech_file_to_array_fn(self, wav_path):
      speech_array, sampling_rate = torchaudio.load(wav_path)
      speech = self.resampler(speech_array).squeeze().numpy()
      return speech
  
file_path: transformers/examples/research_projects/wav2vec2/alignment.py
imports: import argparse
  import os
  from dataclasses import dataclass
  import torch
  import torchaudio
  from tqdm import tqdm
  from transformers import AutoConfig, AutoModelForCTC, AutoProcessor
label_desc: Use image node_id 2 for calling the Wav2Vec2Aligner obj's underlying member method code with example usage: obj.speech_file_to_array_fn(wav_path) and returns: speech