A comparison of how healthy and dysarthric pathological speakers adapt their production is a way to better understand the processes and constraints that interact during speech production in general. The present study focuses on spontaneous speech obtained with varying recording scenarios from five different groups of speakers. Patients suffering from motor speech disorder (dysarthria) affecting speech production are compared to healthy speakers. Three types of dysarthria have been explored: Parkinson's Disease, Amyotrophic Lateral Sclerosis and Cerebellar ataxia. This paper first presents general figures based on syllable-level annotation mining, including detailed information about healthy/pathological speakers variability. Then, we report on the results of automatic timing parsing of interval sequences in speech syllable annotations performed using TGA (Time Group Analysis) methodology. We observed that mean syllable-based speaking rates in time groups for the healthy speakers were higher than those measured in the recordings of dysarthric speakers. The variability in timing patterns (duration regression slopes, intercepts, and nPVI) depended also on the speaking styles in particular populations.