Quantitative analysis of multimodal speech data

This study presents techniques for quantitatively analyzing coordination and kinematics in multimodal speech using video, audio and electromagnetic articulography (EMA) data. Multimodal speech research has flourished due to recent improvements in technology, yet gesture detection/annotation strategies vary widely, leading to difficulty in generalizing across studies and in advancing this field of research. We describe how FlowAnalyzer software can be used to extract kinematic signals from basic video recordings; and we apply a technique, derived from speech kinematic research, to detect bodily gestures in these kinematic signals. We investigate whether kinematic characteristics of multimodal speech differ dependent on communicative context, and we find that these contexts can be distinguis...

from #Head and Neck by Sfakianakis via simeraentaxei on Inoreader https://ift.tt/2q6Q632