The evolution of authoritarian processes: Fostering cooperation in large-scale groups

Authoritarianism, comprising conventionalism, authoritarian submission, and authoritarian aggression, is an important factor underlying prejudice and social discrimination and therefore is typically perceived as socially problematic. In contrast, our work examines adaptive features of authoritarianism. Evolutionary game theoretical considerations (e.g., biased social learning) point to authoritarian psychological processes that establish and foster group life (e.g., high levels of ingroup cooperation). First, the evolution of social learning (particularly conformist and prestige biases) leads to the establishment of local and distinct cultural groups (conventionalism). Second, local cultural rules solve coordination dilemmas by transforming these rules into normative standards against which others are evaluated (authoritarian submission). Third, the common rules within a particular culture or group are reinforced by a tendency to reward norm compliance and punish norm deviations (authoritarian aggression). Implications regarding the deduction of novel research questions as well as dealing with authoritarianism as a social problem are discussed.

Inter-Frame Contextual Modelling For Visual Speech Recognition

In this paper, we present a new approach to visual speech recognition which improves contextual modelling by combining Inter-Frame Dependent and Hidden Markov Models. This approach captures contextual information in visual speech that may be lost using a Hidden Markov Model alone. We apply contextual modelling to a large speaker independent isolated digit recognition task, and compare our approach to two commonly adopted feature based techniques for incorporating speech dynamics. Results are presented from baseline feature based systems and the combined modelling technique. We illustrate that both of these techniques achieve similar levels of performance when used independently. However significant improvements in performance can be achieved through a combination of the two. In particular we report an improvement in excess of 17% relative Word Error Rate in comparison to our best baseline system.