Using Social Signal Processing and Conversational Agent To Aid People in their Negotiation Skills: Self-awareness through Mimicry

Negotiation is not a skill that comes naturally to most people. However, most people could benefit from attaining good negotiation skills. Non-verbal behaviour plays an important role in negotiations. Previous studies have shown a link between mimicry through conversational agents and self-regulation of non-verbal behaviour. The current study aims to raise a person’s self-awareness of their non-verbal behaviour through the medium of a conversational agent in negotiation training. An experiment (N = 64) is conducted where participants performed negotiations with an intermediate feedback round where the participants' non-verbal behaviour was played back on a virtual agent. The agent either mimicked the participants’ non-verbal behaviour or exhibited idle behaviour. It was found that the mimicking agent provided better feedback to the participants. Furthermore, repeated negotiations increase a person's self-awareness. The data indicate that raising a person’s self-awareness in negotiation training by utilising non-verbal mimicry through a conversational agent is feasible.Computer Science | Artificial Intelligenc

Project Delphi: What is Innovation?

Being a company with over 1500 employees, a lot of data is available about people and their day-to-day pursuits, including projects they are working on. Company X has requested to gain more insight into this data, as it is currently scattered over multiple systems. Specifically, they requested to gain insight into which projects have been started around a certain topic, who is involved in these projects, what the status on these projects is and where these projects are carried out inside the company. Company X wants this data represented in a dynamic, scalable and interactive visualisation. To create a product that fulfils the expectations and needs of Company X, a Proof of Concept (PoC) was created. This basic version was used to make sure that Company X and the development team had the same basic idea of the application to be created and was then extended to an Minimal Viable Product (MVP). Having completed this MVP, additional features were implemented. Such features include making the solution generic for different data sources, the ability to filter and search through the data and highlighting/focusing specific data types. In order to ensure that the visualisation can be used instinctively and deliver the information it is meant to, a user study was set up. In this user study, multiple employees of Company X tested the visualisation by completing a set of tasks within the application. By tracking the different results (i.e. number of clicks, time, subjective opinions), the team was able to derive that the application is quite promising, but still had the need for some improvements to explore its full potential.Bachelor ProjectComputer Scienc