Title :
Neural network learning of spectral features of nonverbal speech
Author :
Lerner, Solomon Z. ; Deller, John R.
Author_Institution :
Dept. of Electr. Comput. Eng., Northeastern Univ., Boston, MA, USA
Abstract :
A neural-network approach to the learning of invariant spectral features in cerebral-palsied speech is introduced. The technique is a hybrid conventional digital signal processing/neural network strategy. The objective at this stage is to learn features of nonverbal speech, and to do so in a manner which is robust to the abnormalities of such speech and which is minimally dependent on a priori modeling or parameterization. Thus, it is hoped that these features will be useful as input to a higher-level word recognizer
Keywords :
neural nets; speech analysis and processing; a priori modeling; cerebral-palsied speech; digital signal processing; higher-level word recognizer; neural network learning; nonverbal speech spectral features; parameterization; Character recognition; Computer vision; Convolution; Data mining; Detectors; Frequency; Gray-scale; Neural networks; Speech; Two dimensional displays;
Conference_Titel :
Bioengineering Conference, 1988., Proceedings of the 1988 Fourteenth Annual Northeast
Conference_Location :
Durham, NH
DOI :
10.1109/NEBC.1988.19339
