Adjusting dysarthric speech timing using neural nets

Speech,timing problems,associated,with dysarthria often involve the presence,of periods of extraneous silence and non-speech sounds,as well as inappropriate ly timed or misplaced,speech,gestures. This study evaluated the performance,of neural networks in detecting the presence,of inappropriate or non-speech sounds and extraneous silence. The ‘opt’ neural network,program,[E. Barnard and,R. Cole. OGC Tech. Report No.CSE 89-014] which uses a conjugate gradient algorithm to adjust node weights was,trained to recognize breaths and silence in a reading of the rainbow passage,by a single dysarthric (Cerebral Palsy) talker. Input to the network,consisted of a sequence,of frames of parameters derived from spectral analysis of the speech. The output was,a binary (speech/nonspeech) decision for the segment,of signal corresponding,to the middle frame of the input sequence. Networks of various size and configuration were trained on half the available data and tested on the remaining data. Adjusting Dysarthric Speech Timing using Neural-Nets Applied Science and Engineering Laboratories