Reduced intelligibility is the at the heart of the communication disorder associated with the dysarthrias and other speech production deficits, causing functional and societal limitations and disabilities, and undermining quality of life. At present, the most common clinical approach to intelligibility assessment is subjective in nature. Subjective impressions, although expedient to collect, are by their very nature vulnerable to clinician bias. Safeguards to enhance reliability and validity of subjective impressions (e.g., naive listeners, listen panels, etc) are prohibitively high cost for typical clinical settings. Thee is an urgent need for the development of dependent measures sensitive enough to detect speech changes in early disease;document the efficacy of behavioral, surgical or pharmacological interventions;and track speech changes associated with disease progression. In this translational research, we propose to use the well-developed principles of intelligibility quantification that have been standardized in speech telecommunications and to develop and validate new measures of intelligibility in clinical populations. Specifically, we aim to develop a process by which the intelligibility of dysarthric speech can be validly and reliably quantified relative to a reference control sample;and to algorithmically isolate the source(s) of intelligibiity degradation along certain dimensions to augment clinical practice. In addition to integrating existing intelligibility metrics within our developed framework, we intend to instantiate new metrics, specifically optimized for dysarthric speech, based on insight and data gained during a previous NIH-funded grant. Preliminary results show promise that the proposed approach will yield a successful framework for quantifying intelligibility. These results indicate existing telecommunication-based intelligibility metrics accurately capture intelligibility degradation for noisy speech. Further, we show that the same metrics can accurately capture differences in intelligibility between three dysarthric speakers of differing intelligibility levels. Finally, we how that a subset of the envelope modulation spectra features, developed previously in our lab, are remarkably predictive of a speaker's intelligibility. The results of the proposed research will for the basis for a subsequent R01 proposal for the development of a fully functional clinical tool to objectively quantify and track speech intelligibility and its causal components.

Public Health Relevance

There is an urgent need for the development of dependent measures sensitive enough to detect speech changes in early disease;document the efficacy of behavioral, surgical or pharmacological interventions;and track speech changes associated with disease progression. Reduced intelligibility is the at the heart of the communication disorder associated with the dysarthrias and other speech production deficits, causing functional and societal limitations and disabilities, and undermining quality of life. We aim to develop a process by which the intelligibility of dysarthric speech can be validly and reliably quantified relative to a reference control sample;and to algorithmically isolate the source(s) of intelligibiity degradation along certain dimensions to augment clinical practice.

Agency
National Institute of Health (NIH)
Institute
National Institute on Deafness and Other Communication Disorders (NIDCD)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21DC012558-02
Application #
8515990
Study Section
Special Emphasis Panel (ZDC1-SRB-Y (53))
Program Officer
Shekim, Lana O
Project Start
2012-08-01
Project End
2014-07-31
Budget Start
2013-08-01
Budget End
2014-07-31
Support Year
2
Fiscal Year
2013
Total Cost
$209,257
Indirect Cost
$66,757
Name
Arizona State University-Tempe Campus
Department
Other Health Professions
Type
Schools of Allied Health Profes
DUNS #
943360412
City
Tempe
State
AZ
Country
United States
Zip Code
85287
Berisha, Visar; Liss, Julie; Sandoval, Steven et al. (2014) Modeling Pathological Speech Perception From Data With Similarity Labels. Proc IEEE Int Conf Acoust Speech Signal Process 2014:915-919
Lansford, Kaitlin L; Liss, Julie M (2014) Vowel acoustics in dysarthria: mapping to perception. J Speech Lang Hear Res 57:68-80
Berisha, Visar; Sandoval, Steven; Utianski, Rene et al. (2014) Characterizing the distribution of the quadrilateral vowel space area. J Acoust Soc Am 135:421-7