Technical Program

Paper Detail

Paper:	ITT-L1.2
Session:	Speech Processing Applications
Time:	Thursday, May 18, 16:50 - 17:10
Presentation:	Lecture
Topic:	Industry Technology Track: Speech Recognition
Title:	HMM-Based and SVM-Based Recognition of the Speech of Talkers with Spastic Dysarthria
Authors:	Mark Hasegawa-Johnson, Jon Gunderson, Adrienne Perlman, Thomas Huang, University of Illinois at Urbana-Champaign, United States
Abstract:	This paper studies the speech of three talkers with spastic dysarthria caused by cerebral palsy. All three subjects share the symptom of low intelligibility, but causes differ. First, all subjects tend to reduce or delete word-initial consonants; one subject deletes all consonants. Second, one subject exhibits a painstaking stutter. Two algorithms were used to develop automatic isolated digit recognition systems for these subjects. HMM-based recognition was successful for two subjects, but failed for the subject who deletes all consonants. Conversely, digit recognition experiments assuming a fixed word length (using SVMs) were successful for two subjects, but failed for the subject with the stutter.