Dysarthria

About: Dysarthria is a research topic. Over the lifetime, 2402 publications have been published within this topic receiving 56554 citations.

Measurement of voice onset time in dysarthric patients: methodological considerations.

Abstract: Voice onset time (VOT) reflects the timing control between laryngeal and supralaryngeal adjustments. It has been studied both in normal speakers and patients with speech disorders, but very little inf

Cross-Database Models for the Classification of Dysarthria Presence.

Abstract: Dysarthria is a motor speech disorder that impacts verbal articulation and co-ordination, resulting in slow, slurred and imprecise speech. Automated classification of dysarthria subtypes and severities could provide a useful clinical tool in assessing the onset and progress in treatment. This study represents a pilot project to train models to detect the presence of dysarthria in continuous speech. Subsets of the Universal Access Research Dataset (UA-Speech) and the Atlanta Motor Speech Disorders Corpus (AMSDC) database were utilized in a cross-database training strategy (training on UA-Speech / testing on AMSDC) to distinguish speech with and without dysarthria. In addition to traditional spectral and prosodic features, the current study also includes features based on the Teager Energy Operator (TEO) and the glottal waveform. Baseline results on the UA-Speech dataset maximize wordand participant-level accuracies at 75.3% and 92.9% using prosodic features. However, the cross-training of UA-Speech tested on the AMSDC maximize wordand participant-level accuracies at 71.3% and 90% based on a TEO feature. The results of this pilot study reinforce consideration of dysarthria subtypes in cross-dataset training as well as highlight additional features that may be sensitive to the presence of dysarthria in continuous speech.

Implementing two treatment approaches to childhood dysarthria

Abstract: The paucity of evidence and detail in the literature regarding speech treatment for children with dysarthria due to cerebral palsy (CP) renders it difficult for researchers to replicate studies and make further inroads into this area in need of exploration. Furthermore, for speech-language pathologists (SLPs) wishing to follow treatments that the literature indicates have promise, little guidance is available on the details of the treatments that yielded the positive results. The present article details the implementation of two treatment approaches in speech treatment research for children with dysarthria: Speech Systems Intelligibility Treatment (SSIT) and the Lee Silverman Voice Treatment LOUD (LSVT LOUD). Specific strategies, primarily for treatment, but also for outcome measurement and acoustic analysis of dysarthric speech, are described. These techniques are provided for researchers and clinicians to consider implementing in order to advance speech treatment for this population. New data from research using these approaches are presented, including findings of acoustic vowel space changes following both speech treatments.