code: def split_wav(wav, emotions):
      (
          nchannels,
          sampwidth,
          framerate,
          nframes,
          comptype,
          compname,
      ), samples = wav
  
      left = samples[0::nchannels]
      right = samples[1::nchannels]
  
      frames = []
      for ie, e in enumerate(emotions):
          start = e["start"]
          end = e["end"]
  
          e["right"] = right[
              int(start * framerate) : int(end * framerate)
          ]
          e["left"] = left[
              int(start * framerate) : int(end * framerate)
          ]
  
          frames.append({"left": e["left"], "right": e["right"]})
      return frames
  
file_path: delta/egs/iemocap/emo/v1/local/python/helper.py
imports: import os
  import csv
  import wave
  import sys
  import numpy
  import pandas
  import glob
  from tensorflow.keras.preprocessing.text import text_to_word_sequence
label_desc: Use image node_id 1 for calling a global function with example usage: split_wav(wav, emotions) and returns: frames