VyaktitvaNirdharan: Multimodal Assessment of Personality and Trait Emotional Intelligence

Automatic personality assessment (APA) has immense potential to improve decision-making and human-machine interaction. Numerous techniques for APA have been proposed in existing literature, with prior psychological studies demonstrating convergent validity between personality and trait emotional intelligence (EI). However, to the best of our knowledge, none in APA literature has leveraged this relationship. Further, the primary language for most APA studies is English. To this end, we propose VyaktitvaNirdharan, a multi-modal-multitask learning (MM-MTL) system for predicting personality and EI traits using dyadic conversations in a non-intrusive and near real-time fashion. While most of the previous research has focused on APA for the English language, VyaktitvaNirdharan is also amongst the first to use peer-to-peer conversations in Hindi, a low-resource language. We also show the convergent validity between the predictions of the developed system, confirming that the personality and EI traits estimated by our system preserve the properties of the original traits. Our system can identify the Big-Five and EI traits with average F1-scores of 0.88, and 0.82, respectively. The validity of our findings is further supported by a user study involving 7 stakeholders, including recruiters and clinical psychologists, conducted through a prototype. The proposed system demonstrates promising results and has the potential to aid in improving decision-making in recruitment, mental health wellness and enhance human-machine interaction.