Voice Acoustic Instability During Spontaneous Speech in Parkinson's Disease

J Voice. 2023 Jul 25:S0892-1997(23)00176-5. doi: 10.1016/j.jvoice.2023.06.004. Online ahead of print.


Background: In people with Parkinson's disease (PwPD), both motor and cognitive deficits influence voice and other aspects of communication. PwPD demonstrate vocal instability, but acoustic declines over the course of speaking are not well characterized and the role of cognition on these declines is unknown. We examined voice acoustics related to speech motor instability by comparing the first and the last utterances within a speech task. Our objective was to determine if mild cognitive impairment (MCI) status was associated with different patterns of acoustic change during these tasks.

Methods: Participants with PD (n = 44) were enrolled at University of Massachusetts Chan Medical School and classified by gold-standard criteria as normal cognition (PD-NC) or mild cognitive impairment (PD-MCI). The speech was recorded during the Rainbow Passage and a picture description task (Cookie Theft). We calculated the difference between first and last utterances in fo mean and standardized semitones (STSD), cepstral peak prominence-smoothed (CPPS), and low to high ratio (LH). We used t-tests to compare the declines in acoustic parameters between the task types and between participants with PD-NC versus PD-MCI.

Results: Mean fo, fo variability (STSD) and CPPS declined from the first to the last utterance in both tasks, but there was no significant difference in these declines between the PD-NC and PD-MCI groups. Those with PD-MCI demonstrated lower fo variability on the whole in both tasks and lower CPPS in the picture description task, compared to those with PD-NC.

Conclusions: Mean and STSD fo as well as CPPS may be sensitive to PD-MCI status in reading and spontaneous speech tasks. Speech motor instability can be observed in these voice acoustic parameters over brief speech tasks, but the degree of decline does not depend on cognitive status. These findings will inform the ongoing development of algorithms to monitor speech and cognitive function in PD.

Keywords: Acoustics; Cognition; Motor speech; Parkinson’s disease; Voice.