1. IMRAN KHAN - Department of Telecommunication Engineering, Dawood University of Engineering and Technology,
Karachi, Pakistan.
2. SOHAIL RANA - Department of Electronic Engineering, Dawood University of Engineering & Technology, Karachi,
Pakistan.
3. NADIA MUSTAQIM ANSARI - Department of Electronic Engineering, Dawood University of Engineering & Technology, Karachi,
Pakistan.
4. RIZWAN IQBAL - Department of Telecommunication Engineering, Dawood University of Engineering and Technology,
Karachi, Pakistan.
5. MUHAMMAD ISMAIL - Department of Electronic Engineering, Dawood University of Engineering & Technology, Karachi,
Pakistan.
6. ADNAN WAQAR - Department of Electronic Engineering, Dawood University of Engineering & Technology, Karachi,
Pakistan.
7. SYED WAQAR ALAM - Department of Electronic Engineering, Dawood University of Engineering & Technology, Karachi,
Pakistan.
Understanding human emotions is a key part of human communication and affects our daily life. Scientists and researchers have performed various research to understand the science behind human emotion and how our brain understands different emotions and creates a reaction effect for them. Multilayer Perceptron classifier open-supply toolkits exist for speech popularity and speech processing. Through this research, we improved the accuracy of emotion recognition and attempted to identify the precise emotion of speech files. We created an emotion detection system through an artificial neural network through which different emotions train and self-learn our program for the best efficiency and accuracy. Our program can detect up to 70% - 80% accurate results in our given data.
Speech Emotion Recognition, MLP, Machine Learning, Feature Extraction, Neural Network.