SPEECH RECOGNITION BY FEATURE-ABSTRACTION TECHNIQUES.
Interim rept., for May 63-Jun 64,
RAYTHEON CO WALTHAM MASS
Pagination or Media Count:
A speech-analysis system using analog-threshold logic ATL for feature abstraction has been developed to recognize consonants in utterances of CVC words by a number of talkers. The feature-abstraction networks use a single ATL element for most of the logic functions. The ATL element, originally modeled after the biological neuron, has an output which is linearly proportional to the net sum of excitatory and inhibitory inputs, provided that this net sum is greater than some adjustable threshold. Using networks of ATL elements, both the presence and magnitude of significant features can be abstracted in real time from the speech signals. The recognition equipment is capable of abstracting these features over a 60-db dynamic range from the logarithmitized outputs of 19 low-Q, band-pass filters. The speech-recognition equipment contains more than 500 ATL elements and was designed to operate in real time, to utilize parallel processing in the featureabstraction networks and not to require segmentation. Author