SPEECH RECOGNITION SYSTEM INCLUDING SPEECH SECTION DETECTING SECTION

A trained vector generation section 16 generates beforehand a trained vector v of unvoiced sounds. An LPC Cepstrum analysis section 18 generates a feature vector A of a voice within the non-voice period, an inner product operation section 19 calculates an inner product value VTA between the feature vector A and the trained vector V, and a threshold generation section 20 generates a threshold θv on the basis of the inner product value VTA. Also, the LFC Cepstrum analysis section 18 generates a prediction residual power ε of the signal within the non-voice period, and the threshold generation section 22 generates a threshold THD on the basis of the prediction residual power ε. If the voice is actually uttered, the LPC Cepstrum analysis section 18 generates the feature vector A and the prediction residual power ε, the inner product operation section 19 calculates an inner product value VTA between the feature vector A of input signal Saf and the trained vector V, and a threshold determination section 21 compares the inner product value VTA with the threshold θv and determines the voice section if θv≦VTA. Also, a threshold determination section 23 compares the prediction residual power ε of input signal Saf with the threshold THD and determines the voice section if THD≦ε. The voice section is finally defined if θv≦VTA or THD≦ε, and the input signal Svc for voice recognition is extracted.