When people communicate, their states of mind are coupled with the explicit content of the messages being transmitted. The implicit information conveyed by mental states is essential to correctly understand and frame the communication messages. In mediation, professional mediators include empathy as a fundamental skill when dealing with the relational and emotional aspects of a case. In court environments, emotion analysis intendsto point out stress or fear as indicators of the truthfulness of certain asserts. In commercial environments, such as call-centers, automatic emotional analysis through speech is focused to detect deception or frustration. Computational analysis of emotions focuses on gathering information from speech, facial expressions, body poses and movements to predict emotional states. Specifically, speech analysis has been reported as a valuable procedure for emotional state recognition. While some studies focus on the analysis of speech features to classify emotional states, others concentrate on determining the optimal classification performance. In this paper we analyze current approaches to computational analysis of emotions through speech and consider the replication of their techniques and findings in the domains of mediation and legal multimedia
