A statistical causal model for the assessment of dysarthric speech and the utility of computer-based speech recognition.
The evaluation of the degree of speech impairment and the utility of computer recognition of impaired speech are separately and independently performed. Particular attention is paid to the question concerning whether or not there is a relationship between naive listeners' subjective judgements of impaired speech and the performance of a laboratory version of a speech recognition system. It is a difficult task to relate a speech impairment rating with speech recognition accuracy. Towards this end, a statistical causal model is proposed. This model is very appealing in its structure to support inference, and thus can be applied to perform various assessments such as the success of automatic recognition of dysarthric speech. The application of this model is illustrated with a case study of a dysarthric speaker compared against a normal speaker serving as a control.
Sy
B K
BK
Department of Computer Science, Queens College, Flushing, NY 11367.
Horowitz
D M
DM
D000328:Adult; D003936:Diagnosis, Computer-Assisted / Q000379:methods / Q000706:statistics & numerical data; D004401:Dysarthria / Q000175:diagnosis* / Q000209:etiology; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D015233:Models, Statistical; D013062:Speech Articulation Tests / Q000379:methods / Q000706:statistics & numerical data; D013063:Speech Discrimination Tests / Q000379:methods / Q000706:statistics & numerical data; D013065:Speech Intelligibility