1. A state output probability calculating method for a mixture distribution HMM, executed by a pattern recognition apparatus which performs pattern recognition of an observation signal by using the mixture distribution HMM, wherein an event of a recognition target stored in a memory is modeled in the mixture distribution HMM, comprising: a first output probability calculating step of calculating weighted output probabilities of all distributions belonging to a state for a first observation signal, obtaining a maximum value of the weighted output probabilities and a maximum distribution which outputs the maximum value, and defining the obtained maximum value as an output probability of a mixture distribution; a maximum distribution storage step of storing, in the memory, information which specifies the maximum distribution obtained in the first output probability calculating step; and a second output probability calculating step of calculating only a weighted output probability of the maximum distribution specified by the information stored in the memory in the maximum distribution storage step, for a second observation signal observed after the first observation signal, instead of calculating weighted output probabilities of all distributions, in a case that a predetermined period of time is not elapsed from the time at which the maximum distribution is obtained in the first output probability calculating step, and of defining the calculated weighted output probability calculated in the second output probability calculating step as the output probability of the mixture distribution.