old_contents: import subprocess
  
  class DeepSpeechRecognizer():
      def __init__(self, model=None, alphabet=None, lm=None, trie=None):
          self.model = model
          self.alphabet = alphabet
          self.lm = lm
          self.trie = trie
  
      def recognize(self, audio_file):
          """recognize audio file
  
          args:
              audio_file (str)
  
          return:
              result (str/False)
          """
          output = subprocess.check_output("deepspeech --model {} --alphabet {} --lm {} --trie {} --audio {}".format(self.model, self.alphabet, self.lm, self.trie, audio_file), shell=True, stderr=subprocess.STDOUT)
          for index, line in enumerate(output.split("\n")):
              if line.startswith("Inference took "):
                  return output.split("\n")[index + 1]
          return None
  
  if __name__=="__main__":
      recognizer = DeepSpeechRecognizer(r"models/output_graph.pbmm", r"models/alphabet.txt", r"models/lm.binary", r"models/trie")
      result = recognizer.recognize("audio/8455-210777-0068.wav")
      print(result)
                  
  
  
new_contents: import subprocess
  
  class DeepSpeechRecognizer():
      def __init__(self, model=None, alphabet=None, lm=None, trie=None):
          self.model = model
          self.alphabet = alphabet
          self.lm = lm
          self.trie = trie
  
      def recognize(self, audio_file):
          """recognize audio file
  
          args:
              audio_file (str)
  
          return:
              result (str/False)
          """
          output = subprocess.check_output("deepspeech --model {} --alphabet {} --lm {} --trie {} --audio {}".format(self.model, self.alphabet, self.lm, self.trie, audio_file), shell=True, stderr=subprocess.STDOUT)
          for line in output.split("\n"):
              if line[0].islower():
                  return line
          return None
  
  if __name__=="__main__":
      recognizer = DeepSpeechRecognizer(r"models/output_graph.pbmm", r"models/alphabet.txt", r"models/lm.binary", r"models/trie")
      result = recognizer.recognize("audio/8455-210777-0068.wav")
      print(result)
                  
  
  
subject: change the way to get deepspeech recognize result