A Multi-Smartwatch System for Assessing Speech Characteristics of People with Dysarthria in Group Settings

TL;DR

This paper presents a multi-smartwatch system that captures and analyzes individual speech signals in group settings to assist speech-language pathologists in assessing and treating patients with dysarthria.

Contribution

It introduces a novel technology for blind separation and analysis of mixed speech signals in group environments, tailored for speech disorder assessment.

Findings

Validated on clinical data from Parkinson's patients and controls

Effective separation of mixed speech signals in group settings

Provides detailed speech characteristic metrics

Abstract

Speech-language pathologists (SLPs) frequently use vocal exercises in the treatment of patients with speech disorders. Patients receive treatment in a clinical setting and need to practice outside of the clinical setting to generalize speech goals to functional communication. In this paper, we describe the development of technology that captures mixed speech signals in a group setting and allows the SLP to analyze the speech signals relative to treatment goals. The mixed speech signals are blindly separated into individual signals that are preprocessed before computation of loudness, pitch, shimmer, jitter, semitone standard deviation and sharpness. The proposed method has been previously validated on data obtained from clinical trials of people with Parkinson disease and healthy controls.