Speaker personality classification using systems based on acoustic-lexical cues and an optimal tree-structured Bayesian network
Kartik Audhkhasi, Angeliki Metallinou, Ming Li, Shrikanth Shri Narayanan · 2012
Automatic classification of human personality along the Big Five dimensions is an interesting problem with several prac-tical applications. This paper makes some contributions in this regard. First, we propose a few automatically-derived personality-discriminating lexical features which provide infor-mation complementary to the conventional acoustic-prosodic cues. We also design a frame-level Gaussian mixture model based system which adds complimentary information to the sys-tems trained on global statistical functionals. Next, we note that the Big Five dimensions are correlated and thus model the de-pendency between these dimensions in the form of an optimal tree-structured Bayesian network. Our final sub-system con-sists of within class covariance normalization followed by L1-regularized logistic regression. Fusion of all these sub-systems achieves better classification performance than independently trained classifiers using just acoustic features.