Abstract: An automatic speech recognition system has a multi-mode training capability using a set of previously stored templates of a limited number of predetermined seed words to train the templates for a vocabulary of words. The training speech samples each includes a vocabulary word juxtaposed with a seed word. An averager module maintains an active average template for each of the word units of the training speech samples including the seed word units, and the active average templates are used to continuously update the seed template set as they are used in the training speech samples. The preferred training procedure employs training phrases each having a vocabulary word embedded between two seed words, and two seed template sets are used in succession, the first being composed of single-digit words, and the second composed of carrier words.

Abstract: An apparatus for automatic speech recognition includes a plurality of processors, including template processors in which there are stored templates representative of both speech and non-speech sounds. Incoming sounds are continuously converted into digital signals in respective frames representative of speech and non-speech sounds, respectively. Sequences of such frames are compared with both the speech and non-speech templates to determine the closest matches. Endpoints of respective speech utterances are determined in response to the detection of respective non-speech-speech-non-speech sequences, whereupon such speech utterances are processed to recognize the same.