Negotiation skills training intervention based on automated recognition of human emotion and non-verbal behaviour.

Details and Aims of my research: My research explores the effect of 'social signals' feedback intervention based on automated recognition of affect and non-verbal behaviours within the context of negotiation skills training. In my work I use several off-the-shelf technologies; Sociometric badges, iMotions Biometric Research Platform and Nemesysco Layered Voice Analysis, to recognise and analyse emotional expressions, vocal emotions, and body movement. A controlled experiment is used to compared standard negotiation skills feedback to feedback augmented with emotion and sensor-based social skills evaluation to explore whether negotiation performance and use of social signals vary depending on feedback condition. In my research, I focus on paired-negotiation tasks with three conditions: control (standard feedback) vs. two experimental conditions; one where both negotiators in the pair received the augmented feedback; one where only one of the pair received the augmented feedback. I collect objective and subjective measures of negotiation performance, and emotion and social signals data in order to test the following hypotheses:
Hypothesis 1: measurable changes in social signals will be evident following training in negotiation skills; changes will be greater in those who receive social signals feedback.
Hypothesis 2: training using social signals feedback will result in differences in negotiation outcomes (measured objectively and subjectively).

Future Contributions and Applications: I am looking to find out the extent to which theories of emotion and social signals can be incorporated into practical reality, as well as any potential effects of social signal, voice and facial expressions on negotiation practice and outcomes. Future practical implications of my research are in joint gain negotiation outcomes that could benefit negotiation skills teaching and learning environments.