Reduced intelligibility is at the heart of the communication disorder associated with the dysarthrias and other speech production deficits, undermining quality of life. This research program aims to develop a comprehensive model of intelligibility deficits that offers an explanation for communication failure and success, and thereby identifies targets for remediation, as well as dependent variables that will serve as outcome measures. We have shown that when listeners encounter speech that is difficult to understand, they turn their attention to prosody to help them decide where words begin and end. However this strategy for lexical segmentation becomes challenged when the prosodic information itself is degraded, as in the dysarthrias. Further, the nature of the prosodic degradation predicts the ways in which word boundary identification is impaired. The differences in perceptual error patterns resulting from speech produced by two equally intelligible speakers are predictable and provide information both about the underlying motor deficit and the perceptual representations and strategies of the listener. The present proposal defines this relationship through the development of sensitive dependent variables that predict listener performance patterns and production characteristics. Specifically, we will refine a set of acoustic measures and establish their predictive relationship to perceptual performance (intelligibility and error patterns), using speakers with dysarthria and healthy controls. These automated acoustic measures include measures of based on the low-frequency modulations of the amplitude envelope and measures of fundamental frequency and average spectral variability. This set of acoustic measures will be used to classify speakers by traditional dysarthric subtypes as well as by groupings based on a perceptual-outcome clustering that will be developed using the error patterns obtained from listeners'transcription of each speaker's samples. The model will be tested and refined on a new more diverse group of speakers with intelligibility deficits. The causality of the relationships between acoustics and perception uncovered by these analyses will be tested through perceptual experiments using speech samples that are digitally manipulated to match the prosodic patterns that are associated with particular error types. The proposed project holds promise for immediate clinical impact by providing both sensitive and meaningful outcome measures and an overarching theoretical framework in which to interpret them.
The overall goal of the current project is to develop a theoretically-derived model of intelligibility deficits that has immediate clinical impact by identifying targets for remediation and offering dependent variables that may be used to predict perceptual outcome and track changes in speech due to intervention or disease progression. By defining a set of objective measures that map to meaningful aspects of speech understanding, these dependent variables can be applied to any communication disorder for which intelligibility is reduced.
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| Fletcher, Annalise R; McAuliffe, Megan J; Lansford, Kaitlin L et al. (2017) Assessing Vowel Centralization in Dysarthria: A Comparison of Methods. J Speech Lang Hear Res 60:341-354 |
| Fletcher, Annalise R; McAuliffe, Megan J; Lansford, Kaitlin L et al. (2017) Predicting Intelligibility Gains in Individuals With Dysarthria From Baseline Speech Features. J Speech Lang Hear Res 60:3043-3057 |
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| Lansford, Kaitlin L; Berisha, Visar; Utianski, Rene L (2016) Modeling listener perception of speaker similarity in dysarthria. J Acoust Soc Am 139:EL209 |
| Vitela, A Davi; Monson, Brian B; Lotto, Andrew J (2015) Phoneme categorization relying solely on high-frequency energy. J Acoust Soc Am 137:EL65-70 |
| Carbonell, Kathy M; Lester, Rosemary A; Story, Brad H et al. (2015) Discriminating simulated vocal tremor source using amplitude modulation spectra. J Voice 29:140-7 |
| Utianski, Rene L; Caviness, John N; Liss, Julie M (2015) Cortical characterization of the perception of intelligible and unintelligible speech measured via high-density electroencephalography. Brain Lang 140:49-54 |
| 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 |
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