Recurrence Quantification Analysis of Sentence-Level Speech Kinematics

Abstract

This research note demonstrates the feasibility of using RQA as a tool to compare speech variability across speakers and groups. RQA offers promise as a technique to assess effects of potential stressors (e.g., linguistic or cognitive factors) on the speech production system.

The Impact of Social–Cognitive Stress on Speech Variability, Determinism, and Stability in Adults Who Do and Do Not Stutter

“…Work from our lab (Jackson, Tiede, Riley, & Whalen, 2016) demonstrates the feasibility of using RQA to examine the impact of linguistic stressors on speech in typically developing adult speakers. For a tutorial-like presentation of RQA, including phase space reconstruction, see Webber and Zbilut (2005).…”

“…Second, the STI requires time normalization through the consistent alignment of the beginnings and ends of utterances, which distorts potentially important temporal information (Lucero, 2005;Lucero, Munhall, Gracco, & Ramsay, 1997;Ward & Arnfield, 2001). This is particularly relevant to stuttering because as a group, people who stutter exhibit significantly longer utterance durations or slower speech rates than people who do not stutter (Bloodstein, 1944;Colcord & Adams, 1979;Jackson, 2015;Starkweather & Myers, 1979). Third, the STI holds that there is an inverse relationship between variability in behavior and global stability of the speech motor system (as described in Smith et al, 1995).…”

“…Fluent utterances were those free from atypical and typical disfluencies, hesitations, pauses, interjections, rewording, and aberrant prosody (as in . To further operationalize the categorization of fluency or disfluency, utterances with pauses or gaps exceeding 6% of total utterance duration were considered disfluent (following Jackson, 2015). In that study, 6% was suggested as a threshold because it was the approximate point at which 80% of utterances were selected to be fluent.…”

“…For a tutorial-like presentation of RQA, including phase space reconstruction, see Webber and Zbilut (2005). For an example of RQA applied to speech data, see Jackson et al (2016).…”

“…Following Jackson et al (2016), kinematic signals were sampled at 250 Hz and subsequently low-pass filtered at 10 Hz. Audio signals were low-pass filtered prior to recording using a hardware filter at 7500 Hz and then sampled at 16500 Hz.…”