Parkinsonian Speech and Voice Quality: Assessment and Improvement
Abstract
Parkinson’s disease (PD) is the second most common neurodegenerative disease. Statistics show that nearly 90% of people impaired with PD develop voice and speech disorders. Speech production impairments in PD subjects typically result in hypophonia and consequently, poor speech signal-to-noise ratio (SNR) in noisy environments and inferior speech intelligibility and quality. Assessment, monitoring, and improvement of the perceived quality and intelligibility of Parkinsonian voice and speech are, therefore, paramount. In the first study of this thesis, the perceived quality of sustained vowels produced by PD patients was assessed through objective predictors. Subjective quality ratings of sustained vowels were collected from 51 PD patients, on and off the Levodopa medication, and 7 control subjects. Features extracted from the sustained vowel recordings were combined using linear regression (LR) and support vector regression (SVR). An objective metric that combined linear prediction and harmonicity features resulted in a high correlation of 0.81 with subjective ratings, higher than the performance reported in the literature. The second study focused on the prediction of amplified Parkinsonian speech quality. Speech amplifiers are used by PD patients to counteract hyperphonia. To benchmark the amplifier performance, subjective ratings of the quality of speech samples from 11 PD patients and 10 control subjects using 7 different speech amplifiers in different background noise conditions were collected. Objective quality predictors were then developed in combination with machine learning algorithms such as deep learning (DL). It was shown that the speech amplifiers differentially affect Parkinsonian speech quality and that the composite objective metric resulted in a correlation of 0.85 with subjective speech quality ratings. In the third study, a new signal-to-noise feedback (SNF) device was designed and developed to help PD patients control their speech SNR, intelligibility, and quality. The proposed SNF device contained dual ear-level microphones for estimating the speech SNR, a throat accelerometer for reliable voice activity detection, and visual/auditory alarms when the produced speech was below a certain threshold. Performance evaluation of this device in noisy environments demonstrated significant improvements in speech SNR, perceived intelligibility, and predicted quality, especially in high background noise levels.