Emotion recognition and classification based on audio data using AI

Abstract

In recent years, there has been a growing interest in using artificial intelligence (AI) techniques to develop efficient and accurate models for emotion recognition and classification from audio data. This article presents an overview of advances in the field of emotion recognition and classification using AI with a particular focus on audio data. The article begins by discussing the importance of emotion recognition and its applications in various domains. The technical aspects of emotion recognition from audio data using AI are reviewed. It explores various machine learning and deep learning algorithms such as support vector machines (SVM), recurrent neural networks (RNN) and convolutional neural networks (CNN) that have been successfully used in this context. In addition, the paper focuses on the training and evaluation of emotion recognition models. Potential applications and future directions of emotion recognition and classification based on audio data using AI are discussed. Thus, the paper provides a comprehensive overview of the advances in the field of emotion recognition and classification based on audio data using AI. It highlights the potential of AI techniques in accurately recognising and classifying emotions from audio signals, opening the door to the development of intelligent systems with enhanced human-computer interaction capabilities.