Assessment of Childhood Apraxia of Speech: A Review/Tutorial of Objective Measurement Techniques.

Background With respect to the clinical criteria for diagnosing childhood apraxia of speech (commonly defined as a disorder of speech motor planning and/or programming), research has made important progress in recent years. Three segmental and suprasegmental speech characteristics-error inconsistency, lengthened and disrupted coarticulation, and inappropriate prosody-have gained wide acceptance in the literature for purposes of participant selection. However, little research has sought to empirically test the diagnostic validity of these features. One major obstacle to such empirical study is the fact that none of these features is stated in operationalized terms. Purpose This tutorial provides a structured overview of perceptual, acoustic, and articulatory measurement procedures that have been used or could be used to operationalize and assess these 3 core characteristics. Methodological details are reviewed for each procedure, along with a short overview of research results reported in the literature. Conclusion The 3 types of measurement procedures should be seen as complementary. Some characteristics are better suited to be described at the perceptual level (especially phonemic errors and prosody), others at the acoustic level (especially phonetic distortions, coarticulation, and prosody), and still others at the kinematic level (especially coarticulation, stability, and gestural coordination). The type of data collected determines, to a large extent, the interpretation that can be given regarding the underlying deficit. Comprehensive studies are needed that include more than 1 diagnostic feature and more than 1 type of measurement procedure.

Vocal tract representation in the recognition of cerebral palsied speech.

PURPOSE: In this study, the authors explored articulatory information as a means of improving the recognition of dysarthric speech by machine. METHOD: Data were derived chiefly from the TORGO database of dysarthric articulation (Rudzicz, Namasivayam, & Wolff, 2011) in which motions of various points in the vocal tract are measured during speech. In the 1st experiment, the authors provided a baseline model indicating a relatively low performance with traditional automatic speech recognition (ASR) using only acoustic data from dysarthric individuals. In the 2nd experiment, the authors used various measures of entropy (statistical disorder) to determine whether characteristics of dysarthric articulation can reduce uncertainty in features of dysarthric acoustics. These findings led to the 3rd experiment, in which recorded dysarthric articulation was directly encoded into the speech recognition process. RESULTS: The authors found that 18.3% of the statistical disorder in the acoustics of speakers with dysarthria can be removed if articulatory parameters are known. Using articulatory models reduces phoneme recognition errors relatively by up to 6% for speakers with dysarthria in speaker-dependent systems. CONCLUSIONS: Articulatory knowledge is useful in reducing rates of error in ASR for speakers with dysarthria and in reducing statistical uncertainty of their acoustic signals. These findings may help to guide clinical decisions related to the use of ASR in the future.