ISCA Archive Interspeech 2008
ISCA Archive Interspeech 2008

Combining neural network and rule-based systems for dysarthria diagnosis

James Carmichael, Vincent Wan, Phil Green

This study reports on the development of a diagnostic expert system - incorporating a multilayer perceptron (MLP) - designed to identify any sub-type of dysarthria (loss of neuro-muscular control over the articulators) manifested by a patient undergoing a Frenchay Dysarthria Assessment (FDA) evaluation. If sufficient information is provided describing pathological features of the patient's speech, the rule-based classifier (RBC) can out-perform the MLP in terms of rendering a more accurate and consistent diagnosis. The combination MLP/RBC developed during this study realised an overall improvement in diagnostic accuracy of 9.3% (absolute) for a selection of dysarthric cases, representing a substantial improvement over the benchmark system which - unlike the MLP/RBC - cannot directly process acoustic data.

doi: 10.21437/Interspeech.2008-581

Cite as: Carmichael, J., Wan, V., Green, P. (2008) Combining neural network and rule-based systems for dysarthria diagnosis. Proc. Interspeech 2008, 2226-2229, doi: 10.21437/Interspeech.2008-581

  author={James Carmichael and Vincent Wan and Phil Green},
  title={{Combining neural network and rule-based systems for dysarthria diagnosis}},
  booktitle={Proc. Interspeech 2008},