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Atypical speech prosody is a primary characteristic of autism spectrum disorders (ASD), yet it is often excluded from diagnostic instrument algorithms due to poor subjective reliability. Robust, objective prosodic cues can enhance our understanding of those aspects which are atypical in autism. In this work, we connect objective signal-derived descriptors of prosody to subjective perceptions of prosodic awkwardness. Subjectively, more awkward speech is less expressive (more monotone) and more often has perceived awkward rate/rhythm, volume, and intonation. We also find expressivity can be quantified through objective intonation variability features, and that speaking rate and rhythm cues are highly predictive of perceived awkwardness. Acoustic-prosodic features are also able to significantly differentiate subjects with ASD from typically developing (TD) subjects in a classification task, emphasizing the potential of automated methods for diagnostic efficiency and clarity.