1. A speech recognizing method comprising: a speech section detecting step of detecting a speech section from an input signal; a characteristic amount extracting step of analyzing an input speech, which is the input signal in the speech section, and extracting the time aeries of the amount of characteristics representing characteristics of the input speech; a recognizing target vocabulary comparing step of comparing the time series of the amount of characteristics with respective recognizing target vocabularies read from a recognizing target vocabulary storing unit to store predetermined recognizing target vocabularies one by one to obtain a likelihood that respective recognizing target vocabularies coincide with the time series of the amount of characteristics; an environment adaptive noise model comparing step of comparing the time series of the amount of characteristics with respective environment adaptive noise models read from the environment adaptive noise model storing unit to store predetermined environment adaptive noise models one by one to obtain a likelihood that respective environment adaptive noise models coincide with the time series of the amount of characteristics; a rejection determining step of determining whether or not the input signal is a noise by comparing the likelihood obtained by the recognizing target vocabulary comparing step with the likelihood obtained by environment adaptive noise model comparing step; and wherein the noise model adapting step matches the environment adaptive noise model to the amount of characteristics extracted from the input signal.