It is widely accepted that information derived from analyzing speech (the acoustic signal)
and language production (words and sentences) serves as a useful window into the health …

Spoken responses produced by subjects during neuropsychological exams can provide
diagnostic markers beyond exam performance. In particular, characteristics of the spoken …

Speech-based automatic approaches for evaluating neurological disorders (NDs) depend
on feature extraction before the classification pipeline. It is preferable for these features to be …

Purpose: Over the past decade, the signal processing and machine learning literature has
demonstrated notable advancements in automated speech processing with the use of …

Objective There are many barriers to accessing mental health assessments including cost
and stigma. Even when individuals receive professional care, assessments are intermittent …

Here we seek to automatically identify Hungarian patients suffering from mild cognitive
impairment (MCI) based on linguistic features collected from their speech transcripts. Our …

Introduction Automated computational assessment of neuropsychological tests would
enable widespread, cost‐effective screening for dementia. Methods A novel natural …

Computer-based assessments of natural language afford a framework with which to
measure communication disturbances in adults with severe mental illnesses. Emerging …

In this study we developed an automated system that evaluates speech and language
features from audio recordings of neuropsychological examinations of 92 subjects in the …

This pilot study evaluates the ability of machined learned algorithms to assist with the
differential diagnosis of dementia subtypes based on brief (< 10 min) spontaneous speech …