code: def prepare_FSC(data_folder, save_folder, skip_prep=False):
      """
      This function prepares the Fluent Speech Commands dataset.
  
      data_folder : path to dataset.
      save_folder: folder where the manifest files will be stored.
      skip_prep: If True, skip data preparation
  
      """
      if skip_prep:
          return
  
      splits = [
          "train",
          "valid",
          "test",
      ]
      ID_start = 0  # needed to have a unique ID for each audio
      for split in splits:
          new_filename = os.path.join(save_folder, split) + ".csv"
          if os.path.exists(new_filename):
              continue
          logger.info("Preparing %s..." % new_filename)
  
          ID = []
          duration = []
  
          wav = []
          wav_format = []
          wav_opts = []
  
          spk_id = []
          spk_id_format = []
          spk_id_opts = []
  
          semantics = []
          semantics_format = []
          semantics_opts = []
  
          transcript = []
          transcript_format = []
          transcript_opts = []
  
          df = pd.read_csv(
              os.path.join(data_folder, "data", split) + "_data.csv"
          )
          for i in range(len(df)):
              ID.append(ID_start + i)
              signal = read_audio(os.path.join(data_folder, df.path[i]))
              duration.append(signal.shape[0] / 16000)
  
              wav.append(os.path.join(data_folder, df.path[i]))
              wav_format.append("wav")
              wav_opts.append(None)
  
              spk_id.append(df.speakerId[i])
              spk_id_format.append("string")
              spk_id_opts.append(None)
  
              transcript_ = df.transcription[i]
              transcript.append(transcript_)
              transcript_format.append("string")
              transcript_opts.append(None)
  
              semantics_ = (
                  '{"action:" "'
                  + df.action[i]
                  + '"| "object": "'
                  + df.object[i]
                  + '"| "location": "'
                  + df.location[i]
                  + '"}'
              )
              semantics.append(semantics_)
              semantics_format.append("string")
              semantics_opts.append(None)
  
          new_df = pd.DataFrame(
              {
                  "ID": ID,
                  "duration": duration,
                  "wav": wav,
                  "spk_id": spk_id,
                  "semantics": semantics,
                  "transcript": transcript,
              }
          )
          new_df.to_csv(new_filename, index=False)
          ID_start += len(df)
  
imports: import os
  import logging
  from speechbrain.dataio.dataio import read_audio
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_FSC(data_folder, save_folder, skip_prep) without return types