Automatic Evaluation of Speech Rhythm Instability and Acceleration in Dysarthrias Associated with Basal Ganglia Dysfunction
Abstract
Speech rhythm abnormalities are commonly present in patients with different neurodegenerative disorders. These alterations are hypothesized to be a consequence of disruption to the basal ganglia circuitry involving dysfunction of motor planning, programing, and execution, which can be detected by a syllable repetition paradigm.
Therefore, the aim of the present study was to design a robust signal processing technique that allows the automatic detection of spectrally distinctive nuclei of syllable vocalizations and to determine speech features that represent rhythm instability (RI) and rhythm acceleration (RA). A further aim was to elucidate specific patterns of dysrhythmia across various neurodegenerative disorders that share disruption of basal ganglia function.
Speech samples based on repetition of the syllable /pa/ at a self-determined steady pace were acquired from 109 subjects, including 22 with Parkinson's disease (PD), 11 progressive supranuclear palsy (PSP), 9 multiple system atrophy (MSA), 24 ephedrone-induced parkinsonism (EP), 20 Huntington's disease (HD), and 23 healthy controls. Subsequently, an algorithm for the automatic detection of syllables as well as features representing RI and RA were designed.
The proposed detection algorithm was able to correctly identify syllables and remove erroneous detections due to excessive inspiration and non-speech sounds with a very high accuracy of 99.6%. Instability of vocal pace performance was observed in PSP, MSA, EP, and HD groups.
Significantly increased pace acceleration was observed only in the PD group. Although not significant, a tendency for pace acceleration was observed also in the PSP and MSA groups.
Our findings underline the crucial role of the basal ganglia in the execution and maintenance of automatic speech motor sequences. We envisage the current approach to become the first step toward the development of acoustic technologies allowing automated assessment of rhythm in dysarthrias