An improved isolation word recognition system based upon the linear prediction residual

The linear prediction residual has been shown to be an effective technique for isolated word recognition. This paper develops a new spectral interpretation of this method for waveform matching, describes how the accuracy of such a system can be increased by training on multiple repetitions of the reference vocabulary, and how both the reference parameter storage requirements and computation rate can be reduced in half by omitting redundant speech information. Results of experiments vary from a low of 88% when the vocabulary consisted of 25 pairs of rhyming words differing only by the initial consonant sound, to a high of 98.1% when the vocabulary consisted of 107 flight commands having an average of two syllables per word.