Recently, cognitive science researchers have revealed that
human cognition involves the body and is a kind of self-
organization phenomenon emerging from dynamic interaction
across body-brain-environment. Some of the data obtained
from such cognitive, behavioral, or physiological activities
are often complicated in terms of non-stationarity and
nonlinearity. Researchers have proposed several analytical
tools and frameworks. Recurrence analysis is one of the
nonlinear data analyses developed in nonlinear dynamics. It
has been applied to various research fields, including
cognitive science, for language (categorical) data or motion
(continuous) data. However, most previous studies have
applied recurrence methods individually to categorical or
continuous data. We aimed to integrate these methods to
investigate the relationship between speech (categorical) and
motion (continuous) directly. To do so, we added temporal
information (a time stamp) to categorical data and applied the
joint recurrence analysis methods to visualize and quantify
speech-motion coordination during a rap performance. Our
pilot study suggested the possibility of visualizing and
quantifying it.