code: def max_alignment(s1, s2, skip_character="~", record=None):
      """
      A clever function that aligns s1 to s2 as best it can. Wherever a character from s1 is not found in s2, a '~' is
      used to replace that character.
  
      Finally got to use my DP skills!
      """
      if record is None:
          record = {}
      assert (
          skip_character not in s1
      ), f"Found the skip character {skip_character} in the provided string, {s1}"
      if len(s1) == 0:
          return ""
      if len(s2) == 0:
          return skip_character * len(s1)
      if s1 == s2:
          return s1
      if s1[0] == s2[0]:
          return s1[0] + max_alignment(
              s1[1:], s2[1:], skip_character, record
          )
  
      take_s1_key = (len(s1), len(s2) - 1)
      if take_s1_key in record:
          take_s1, take_s1_score = record[take_s1_key]
      else:
          take_s1 = max_alignment(s1, s2[1:], skip_character, record)
          take_s1_score = len(take_s1.replace(skip_character, ""))
          record[take_s1_key] = (take_s1, take_s1_score)
  
      take_s2_key = (len(s1) - 1, len(s2))
      if take_s2_key in record:
          take_s2, take_s2_score = record[take_s2_key]
      else:
          take_s2 = max_alignment(s1[1:], s2, skip_character, record)
          take_s2_score = len(take_s2.replace(skip_character, ""))
          record[take_s2_key] = (take_s2, take_s2_score)
  
      return (
          take_s1
          if take_s1_score > take_s2_score
          else skip_character + take_s2
      )
  
imports: import torch
  import torchaudio
  from transformers import Wav2Vec2CTCTokenizer, Wav2Vec2FeatureExtractor, Wav2Vec2ForCTC
label_desc: Use image node_id 1 for calling a global function with example usage: max_alignment(s1, s2, skip_character, record) and returns: unknown, str, unknown, s1, unknown