text: from collections import Counter
  import spacy
  nlp = spacy.load('en_core_web_sm')
  from num2words import num2words
  from word2number import w2n
  
  srt = []
  with open('./prototype.srt') as reader: 
      srt = reader.readlines()
  
  allText = {}
  key = 0
  gotTimestamp = False
  timestamp = ""
  text = ""
  for line in srt:
      if line == "\n": 
          allText[key] = [timestamp, text]
          key = 0
          text = ""
          timestamp = ""
          gotTimestamp = False
      elif key == 0: 
          key = int(line)
      elif not gotTimestamp:
          timestamp = line
          gotTimestamp = True
      else: 
          line = line.replace("--", "")
          text += line
  
  for key,value in allText.items(): 
      words = "" 
      text = value[1]
      text = text.replace("1 in 10 meals", "\\bold" + "1 in 10 meals" + "\\bold")
      text = text.replace("fewer than", "\\bold" + "fewer than" + "\\bold")
      text = text.replace("650 calories", "\\bold" + "650 calories" + "\\bold")
      text = text.replace("The spike around 1000 calories", "\\bold" + "The spike around 1000 calories" + "\\bold")
      splitWords = text.split(" ")
      for word in splitWords: 
          words += word + " "
      print("words " + words)
      allText[key] = [value[0], words]
  
  with open('./output.srt', "w") as srt:
      for key, value in allText.items():
          srt.writelines(str(key) + "\n")
          srt.writelines(value[0])
          srt.writelines(value[1])
          srt.writelines("\n")
  
  with open('./output.txt', "w") as phrases:
      phrases.writelines("1 in 10 meals\n")
      phrases.writelines("fewer than")
      phrases.writelines(" 650 calories\n")
      phrases.writelines("The spike around 1000 calories")
  
  # print(words)