where the approximation is based on the nth order Markov assumption.
when we predict the current word w i , we only consider the pre- Different from the forward n-gram language model, the backward n-gram language model assigns a probability P b (w m 1 ) to w m 1 by looking at the succeeding context according to For the convenience of training, we invert the order in each sentence in the training data, i.e., from the original order (w 1 ...w m ) to the reverse order (w m ...w 1 ).