code: def EDER(prediction, id, duration, emotion, window_length, stride):
      """Calculates the EDER value
  
      Args:
          prediction (list): a list of frame-wise predictions of the utterance
          id (str): id of the utterance
          duration (float): duration of the utterance
          emotion (list of dicts): the ground truth emotion and its duration,
              e.g. [{'emo': 'angry', 'start': 1.016, 'end': 6.336}]
          window_length (float): the frame length used for frame-wise prediction
          stride (float): the frame length used for frame-wise prediction
  
      Returns:
          float: the calculted EDER for the utterance
  
      Example
      -------
      >>> from speechbrain.utils.EDER import EDER
      >>> prediction=['n', 'n', 'n', 'a', 'a', 'a']
      >>> id="spk1_1"
      >>> duration=1.22
      >>> emotion=[{'emo': 'angry', 'start': 0.39, 'end': 1.10}]
      >>> window_length = 0.2
      >>> stride = 0.2
      >>> EDER(prediction, id, duration, emotion, window_length, stride)
      0.2704918032786885
      """
  
      duration = float(duration)  # for recipe tests
      lol = []
      for i in range(len(prediction)):
          start = stride * i
          end = start + window_length
          lol.append([id, start, end, prediction[i]])
  
      lol = merge_ssegs_same_emotion_adjacent(lol)
      if len(lol) != 1:
          lol = distribute_overlap(lol)
  
      ref = reference_to_lol(id, duration, emotion)
  
      good_preds = 0
      for i in ref:
          candidates = [
              element for element in lol if element[3] == i[3]
          ]
          ref_interval = [i[1], i[2]]
  
          for candidate in candidates:
              overlap = getOverlap(
                  ref_interval, [candidate[1], candidate[2]]
              )
              good_preds += overlap
      return 1 - good_preds / duration
  
label_desc: Use image node_id 1 for calling a global function with example usage: EDER(prediction, id, duration, emotion, window_length, stride) and returns: unknown