MULTI-MODAL EMOTION RECOGNITION ON IEMOCAP WITH NEURAL NETWORKS.

Emotion recognition has become an important field of re- search in Human Computer Interactions and there is a grow- ing need for automatic emotion recognition systems. One of the directions the research is heading is the use of Neural Networks which are adept at estimating complex functions that depend on a large number and diverse source of input data. In this paper we attempt to exploit this effectiveness of Neural networks to enable us to perform multimodal Emotion recognition on IEMOCAP dataset using data from Speech, Text, and Motions captured from face expressions, rotation and hand movements. Prior research has concentrated on Emotion detection from Speech on the IEMOCAP dataset, but our approach uses the multiple modes of data offered by IEMOCAP for a more robust and accurate emotion detection