# Perception of dysarthric speech: An objective model of dysarthric speech evaluation with actionable outcomes

> **NIH NIH R01** · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · 2020 · $307,097

## Abstract

The trained ear of the speech-language pathologist is the gold standard assessment tool for clinical practice in
motor speech disorders. However, perceptual judgments are vulnerable to bias and their relationship with
estimates of listener intelligibility – the final arbiter of speech goodness – is indeterminate. Interpretable,
objective, and robust outcome measures that provide targets for treatment are urgently needed in order to
provide more precise care and reliably monitor patient progress. Based on theoretical models of speech
perception, in our previous grants we have developed a novel set of outcome measures that provide a multi-
dimensional intelligibility profile (MIP) by using custom speech stimuli and a new coding strategy that allows us
to capture the types of errors that listeners make when listening to dysarthric speech. This has led to a more
complete intelligibility profile that codifies these errors at different levels of granularity, from global to discrete.
Simultaneously, we have also developed a computational model for evaluation of dysarthric speech capable of
reliably estimating a limited set of intelligibility measures directly from the speech acoustics. To date, both the
outcome measures and the objective model have been evaluated on cross-sectional data only. In this renewal
application, our principal goal is to evaluate specific hypotheses regarding expected changes in this
multidimensional intelligibility profile as a result of different intervention instruction conditions (loud, clear,
slow). A secondary goal of the proposal is to further refine our objective model to predict the complete
intelligibility profile and to evaluate its ability to detect intelligibility changes within individual speakers. This is
critical for clinicians who currently have no objective ways to assess the value of their interventions. With the
aim of improving the standard of care through technology, the long-term goal of this proposal is to develop
stand-alone objective outcome measures for dysarthria that can provide clinicians with reliable treatment
targets. Such applications have the potential to dramatically alter the current standard of care in speech
pathology for patients with neurological disease or injury. Furthermore, these applications also have the
potential to reduce health disparities by partially automating clinical intervention and providing easier access to
these services to those in remote areas or in underdeveloped countries.

## Key facts

- **NIH application ID:** 9850868
- **Project number:** 5R01DC006859-14
- **Recipient organization:** ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
- **Principal Investigator:** Visar Berisha
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $307,097
- **Award type:** 5
- **Project period:** 2004-07-01 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9850868

## Citation

> US National Institutes of Health, RePORTER application 9850868, Perception of dysarthric speech: An objective model of dysarthric speech evaluation with actionable outcomes (5R01DC006859-14). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9850868. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*