The hidden Markov model assumes that the world consists of a kinds of phenomenons that we can observe and a kinds of phenomenons that we can not observe or hard to observe. Under these assumptions, the hidden Markov model has shown an excellent effect in the interpretation of time series data. In this presentation, we propose a variation of hidden Markov model and give an estimation algorithm for the variation.