Survey on Emotion Detection via Audio Processing and Deep Learning

Abstract

The expanding incorporation of speech and audio data in numerous applications is heavily dependent on Machine Learning (ML) and Artificial Intelligence (AI). The complexity of audio data analysis in machine learning stems from noise and variability, necessitating preprocessing and feature extraction techniques. These features enable machine learning algorithms to identify and recognize audio patterns. This study provides an overview of audio data processing and deep learning techniques used for emotion detection. This research presents a machine learning model for emotion detection, describes the model in detail, and explores anticipated results and potential avenues for further investigation.