code: def match_error_rate(
      preds: Union[str, List[str]], target: Union[str, List[str]]
  ) -> Tensor:
      """Match error rate is a metric of the performance of an automatic speech recognition system.
  
      This value indicates the percentage of words that were incorrectly predicted and inserted. The lower the value, the
      better the performance of the ASR system with a MatchErrorRate of 0 being a perfect score.
  
      Args:
          preds: Transcription(s) to score as a string or list of strings
          target: Reference(s) for each speech input as a string or list of strings
  
      Returns:
          Match error rate score
  
      Examples:
          >>> preds = ["this is the prediction", "there is an other sample"]
          >>> target = ["this is the reference", "there is another one"]
          >>> match_error_rate(preds=preds, target=target)
          tensor(0.4444)
  
      """
      errors, total = _mer_update(
          preds,
          target,
      )
      return _mer_compute(errors, total)
  
imports: from typing import List, Tuple, Union
  import torch
  from torch import Tensor, tensor
  from torchmetrics.functional.text.helper import _edit_distance
label_desc: Use image node_id 3 for calling a global function with example usage: match_error_rate(preds, target) and returns: _mer_compute