Acoustic Speech Analytics Are Predictive of Cerebellar Dysfunction in Multiple Sclerosis.

Area of Science:

• Neuroscience
• Neurology
• Speech Science

Background:

• Speech production is linked to cerebellar function, a brain region often impaired in multiple sclerosis (MS).
• Speech abnormalities are common in MS, but their potential for monitoring cerebellar function is underexplored.
• Objective speech analysis offers a promising avenue for assessing neurological conditions.

Purpose of the Study:

• To develop an objective speech score reflecting cerebellar function, pathology, and quality of life in MS patients.
• To investigate the relationship between speech characteristics and clinical/imaging measures of cerebellar impairment.
• To assess the utility of speech metrics in monitoring disease progression and impact in MS.

Main Methods:

• Eighty-five MS patients and 21 controls underwent acoustic speech analysis and listener ratings.
• Cerebellar function, disability, and pathology were assessed using clinical scores and MRI.
• Speech variables were modeled to predict cerebellar function, forming a composite speech score.

Main Results:

• Slow syllable repetition rate and increased pause percentage were key predictors of cerebellar impairment.
• The composite speech score explained 54% of the variation in cerebellar function.
• The score correlated with cerebellar white matter volume, quality of life, and accurately predicted motor impairment (85% accuracy).

Conclusions:

• An objective, multi-feature speech metric effectively represents motor cerebellar impairment in MS.
• Speech analysis can serve as a valuable, non-invasive tool for monitoring cerebellar health in MS.
• This approach may enhance understanding and management of neurological conditions affecting speech.