Measures of Voice Quality as Indicators of Mild Cognitive Impairment

Noticeable decline in communication skills of patients with Alzheimer’s disease are often observed in the early stages of the disease, years before the dementia emerges. Prior literature has identified language abnormalities such as decline of linguistic ability or syntactic deficits influenced by the cognitive impairment. While language‐related measures are able to characterize spoken words of speech samples, they are inherently incapable of quantifying the voice‐related properties such as emotion or voice quality. Focusing on automatically derived voice‐based biomarkers that reflect the voicing quality of speakers, our objective is to explore the usefulness of these measures at detecting mild cognitive impairment (MCI) as early indicators of MCI in machine learning models. We hypothesize that cognitive impairment influences the individual’s voice quality resulting in an abnormal periodicity in speech often known as vocal dysperiodicity.