Speech/non-speech (S/NS) detection plays the important role for
automatic speech recognition (ASR) system, especially in the case
of isolated words or commands recognition. Even in continuous
speech a S/NS decision can be made at the beginning and at the end
of a sequence resulting in a "sleep mode" of the speech recognizer
during the silence and in a reduction of computation demands. It
is very difficult, however, to precisely locate the endpoints of
the input utterance because of unpredictable background noise. In
the proposed method in this paper, we make use of the advantages
of two approaches (i.e. to try to find the best set of heuristic
features and apply a statistical induction method) for the best
S/NS decision.