8. The method of claim 7 , wherein the external embedding neural network language model determines the predicted current word as a conditional probability mass function as follows: 
 P ( w i |w i−2 , w i−1 )= s ( h i R P G ), where s is a soft-max function, h i is an output of the hidden layer, and R P G is the concatenation of the external embedding matrix to the prediction word embedding matrix.
8. The method of claim 7 , wherein the external embedding neural network language model determines the predicted current word as a conditional probability mass function as follows: 
 P ( w i |w i−2 , w i−1 )= s ( h i R P G ), where s is a soft-max function, h i is an output of the hidden layer, and R P G is the concatenation of the external embedding matrix to the prediction word embedding matrix. 9. The method of claim 8 , wherein the external embedding neural network language model determines the concatenation of the external embedding matrix to the prediction word embedding matrix, R P G as follows: 
 R P G =[G R P T ] T , where G is the external word embedding matrix and R P is the prediction word embedding matrix.