The bigram topic model of Wallach (2006) simply replaces this unigram word distribution (a multinomial) for each topic with a bigram word distribution 1 .
ordinary LDA generates word conditioning only on the latent topic, whereas the bigram topic model generates conditioning on both the latent topic and the previous word, as in the bigram language model.