Complexity matching in speech: Effects of speaking rate and naturalness

Abstract

Recordings of speech exhibit nested clustering of peak amplitude events that reflects the hierarchical temporal structure of language. Previous studies have found variations in nested clustering to correspond with variations in prosody and social interaction. In the present study, we tested two specific dimensions of variation in speech hypothesized to have differing effects on hierarchical temporal structure: Speaking rate and naturalness. Rate was manipulated both algorithmically and experimentally, and naturalness was manipulated using synthesized speech, with sine wave speech as a comparison. Allan Factor analysis was used to quantify nested clustering of peak amplitude events in speech recordings as a function of timescale. For fast speech, nested clustering was found to shift into shorter timescales, whereas for synthesized speech, nested clustering was found to decrease in the longer timescales. Results are discussed in terms of complexity matching and its implications for how neural and perceptual processes might respond to changes in the hierarchical temporal structure of speech signals.