Topic Mining based on Word Posterior Probability in Spoken Document
For speech recognition system, there are three kinds of result representations as one-best, N-best and Lattice. Since lattice has multi-path which can reduce the effect of recognition error rate, it is widely applied nowadays. In fact, there are amount of redundancies in lattice, which leads to the increasing of complexity of latter algorithm based on it. Additionally, for the decoding algorithm, it is acted as Maximum A Posterior probability (MAP) which can only guarantee the posterior probability of the whole sentence is of maximum.