Portfolio

This is my final year thesis project. In this project, I tried to show a comparative analysis on speech emotion recognition. Here, We worked on IEMOCAP dataset which was realized by the University of Southern California .  The dataset has three types of data: text, audio,  and video.  We worked on the only text and audio dataset.  The abstract part is given below. Abstract —   Recently, speech recognition has been one of the most necessary domains in machine learning and deep learning. People tend to order a machine by speech more comfortably and so this field has emerged to fulfill this necessity. In this paper, we proceed towards a feature engineering-based approach for detecting emotion in speech domain. Handcrafted features from multiple audio files are inclined to feed into learning models Features extracted from text domain are also included for resolving ambiguity. We follow both machine learning and deep learning-based approach where extracted fe...