I have an LSTM model. This model takes as input tokens. Those tokens represent XML markups extracted from some XML files. My model is working fine. However, I want to optimize it by adding word embedding as additional features to the LSTM model. Does it make sense to combine word embeddings and encoded tokens (encoded as integers) for the LSTM model ?