Paper Title
Speech Emotional Recognition using Pre-Trained Deep Learning Models

To understand human emotion through speech, it is often underestimated that humans have the capability to understand a basic set of emotions just from how they are spoken or in what tone it is spoken. While on the other hand when it comes to modern day machines (i.e. computers) it is a task that is stilla very hard process simply because of the many variables which differ in the sound wave as people talk to each other. A great part in understanding a speech is to understand the emotion behind the speech which the speaker is trying to convey. Our main goal in this study is to find emotion behind the speech using advanceddeep learning algorithms. We have used a popular datasets viz. RAVDESS, TESS, SAVEE to test out or model.The model is trained in such manner that a set of eight emotions (neutral, calm, happy, sad, angry, fearful, disgust, surprise) which can be classified by the aforementioned model.Our best and worst results are obtained by Resnet i.e. 82% and MobileNet i.e. 47%, respectively. In order for further research we have created a github repository which can be accessed via