Abstract

In human–human interactions, entrainment is a naturally occurring phenomenon that happens when interlocutors mutually adapt their behaviors through the course of an interaction. This mutual behavioral dependency has been at the center of psychological studies of human communication for decades. Quantitative descriptors of the degree of entrainment can provide psychologists an objective method to advance studies of human communication including in mental health domains. However, the subtle nature of the entrainment phenomenon makes it challenging for computing such an effect based on just human annotations. In this paper, we propose an unsupervised signal-derived approach within a principal component analysis framework for quantifying one aspect of entrainment in communication, namely, vocal entrainment. The proposed approach to quantify the degree of vocal entrainment involves …

Date

March 1, 2014

Authors

Chi-Chun Lee, Athanasios Katsamanis, Matthew P Black, Brian R Baucom, Andrew Christensen, Panayiotis G Georgiou, Shrikanth S Narayanan

Journal

Computer Speech & Language

Volume

28

Issue

2

Pages

518-539

Publisher

Academic Press