1. A speech recognition method, comprising the following steps: inputting a speech signal; using a processor to process the following: a reference step of referring to, in a computation of a likelihood of an acoustic model referred to upon computing an accumulated likelihood of a hypothesis, at least one subword model determined depending on its context subwords with respect to each hypothesis; a first likelihood-computation step of computing, based on the input speech signal to be recognized and each of the subword models, likelihoods of acoustic models of the respective subword models, and setting a maximum value of the computed likelihoods as a likelihood of an acoustic model corresponding to the hypothesis; a storing step of storing the subword model exhibiting the maximum value; and if a predetermined condition is satisfied, a second likelihood computation step is performed instead of the first likelihood computation step, the second likelihood computation step including computing a likelihood of the stored subword model and setting the likelihood of the stored subword model as a likelihood of an acoustic model corresponding to the hypothesis, wherein the predetermined condition includes that a time elapsed from the execution of the first likelihood computation step is not longer than a predetermined period and that a difference between an observation signal serving as a target in the first likelihood computation step that is last and a present observation signal is not greater than a predetermined value; and outputting a recognition result based on the process.