Correlating Perceptual Voice Quality in Adductor Spasmodic Dysphonia With Computer Vision Assessment of Glottal Geometry Dynamics.

Purpose: This study examined the relationship between voice quality and glottal geometry dynamics in patients with adductor spasmodic dysphonia (ADSD).

Method: An objective computer vision and machine learning system was developed to extract glottal geometry dynamics from nasolaryngoscopic video recordings for 78 patients with ADSD. General regression models were used to examine the relationship between overall voice quality and 15 variables that capture glottal geometry dynamics derived from the computer vision system.

The Influence of Linguistic Demand on Symptom Expression in Adductor Spasmodic Dysphonia.

Introduction: Adductor Spasmodic Dysphonia (ADSD), a form of focal dystonia, has been defined as a neurogenic, task-specific disorder characterized by abrupt spasms of intrinsic laryngeal muscles that result in phonatory breaks. Voice breaks are typically isolated to propositional speech, and reported to increase in severity as speaking demand or complexity increases. Research to date has focused on variations in phonologic contexts and their influence on voice breaks.