基于机器翻译、语音识别和语音合成技术，构建机器翻译系统

def preprocess(text):
  text = text.lower()
  text = text.replace(',', '').replace('.', '')
  words = text.split(' ')
  word_to_id = {}
  id_to_word = {}
  for word in words:
    if word not in word_to_id:
      new_id = len(word_to_id)
      word_to_id[word] = new_id
      id_to_word[new_id] = word
  corpus = np.array([word_to_id[w] for w in words])
  return corpus, word_to_id, id_to_word
  
def create_co_matrix(corpus, vocab_size, window_size=1):
  corpus_size = len(corpus)
  co_matrix = np.zeros((vocab_size, vocab_size), dtype=np.int32)
  for idx, word_id in enumerate(corpus):
    for i in