What are the advantages for working with LSTM with Word embedding and just LSTM

Question

I am a beginner in Tensorflow. I am working on a dataset for sentiment analysis. I have used two kinds of methods one is LSTM and the other is LSTM with pre-trained word embeddings like (GloVe & Fast Text). I can see there is a difference of accuracy. But can anyone explain what are the advantages of working with pre-trained word embeddings with LSTM over just LSTM.