Automated analysis of natural speech in amyotrophic lateral sclerosis spectrum disorders.

Objective: We implemented automated methods to analyze speech and evaluate the hypothesis that cognitive and motor factors impair prosody in partially distinct ways in patients with amyotrophic lateral sclerosis (ALS).

Methods: We recruited 213 participants, including 67 with ALS (44 with motor ALS, 23 with ALS and frontotemporal degeneration [FTD]), 33 healthy controls, and neurodegenerative reference groups with behavioral variant FTD (n = 90) and nonfluent/agrammatic primary progressive aphasia (n = 23). Digitized, semistructured speech samples obtained from picture descriptions were automatically segmented with a Speech Activity Detector; continuous speech segments were pitch-tracked; and duration measures for speech and silent pause segments were extracted. Acoustic measures were calculated, including fundamental frequency (f0) range, mean speech and pause segment durations, total speech duration, and pause rate (pause count per minute of speech). Group comparisons related performance on acoustic measures to clinical scales of cognitive and motor impairments and explored MRI cortical thinning in ALS and ALS-FTD.

Results: The f0 range was significantly impaired in ALS spectrum disorders and was related to bulbar motor disease, and regression analyses related this to cortical thickness in primary motor cortex and perisylvian regions. Impaired speech and pause duration measures were related to the degree of cognitive impairment in ALS spectrum disorders, and regressions related duration measures to bilateral frontal opercula and left anterior insula.

Conclusion: Automated analyses of acoustic speech properties dissociate motor and cognitive components of speech deficits in ALS spectrum disorders.