1. A speech recognizing apparatus comprising: a speech section detecting unit to detect a speech section from an input signal; a characteristic amount extracting unit to analyze an input speech, which is the input signal in the speech section, and extracting the time series of the amount of characteristics representing the characteristics of the input speech; a recognizing-unit standard pattern storing unit to store recognizing-unit standard patterns; a recognizing target vocabulary storing unit to store predetermined recognizing target vocabularies; a recognizing target vocabulary comparing unit to compare one by one the time series of the amount of characteristics obtained by the characteristic amount extracting unit with one recognizing-unit standard pattern or with two or more recognizing-unit standard patterns stored in the recognizing-unit standard pattern storing unit, combined on the basis of the recognizing target vocabularies stored in the recognizing target vocabulary storing unit, to obtain a likelihood that the respective recognizing-unit standard patterns coincide with the time series of the amount of characteristics; an environment adaptive recognizing-unit selecting unit to select at least one recognizing-unit standard patterns adaptive to an environmental noise, stored in the recognizing-unit standard pattern storing unit; an environment adaptive noise model comparing unit to compare one by one the time series of the amount of characteristics obtained by the characteristic amount extracting unit with one selected recognizing-unit standard pattern or two or more recognizing-unit standard patterns selected by the environment adaptive recognizing-unit selecting unit and combined, to obtain a likelihood that the respective recognizing-unit standard patterns coincide with the time series of the amount of characteristics; an optimal phoneme series comparing unit to compare one by one the time series of the amount of characteristics inputted from the characteristic amount extracting unit with one recognizing-unit standard pattern or with two or more combined recognizing-unit standard patterns, stored in the recognizing-unit standard pattern storing unit, to obtain a likelihood that the respective recognizing-unit standard patterns coincide with the time series of the amount of characteristics; a first rejection determining unit to determine whether or not the input signal is a noise, on the basis of the likelihood of coincidence obtained by the recognizing target vocabulary comparing unit; and a second rejection determining unit to determine whether or not an input signal determined not to be noise by the first rejection determining unit is a noise, on the basis of the likelihood of coincidence obtained by the recognizing target vocabulary comparing unit and the likelihood of coincidence obtained by the environment adaptive noise model comparing unit, wherein, when the first or second rejection determining unit determines the input signal to be a noise, the environment adaptive recognizing-unit selecting unit adaptively updates order of selection of the recognizing-unit standard pattern on the basis of the likelihood of coincidence obtained by the optimal phoneme series comparing unit.