AI-BASED MOOD DETECTION FROM VOICE: AN ALGORITHMIC APPROACH

In this paper, an AI- based sentiment analysis algorithm is introduced. The study centers on data collecting, pre-processing, feature engineering, model choosing, training, evaluating and implementing as well as iteratively updating. We investigate the efficacy of machine learning models such as Convolutional neural networks (CNNs), Recurrent Neural Networks (RNNs) and Support Vector Machines (SVM) for sentiment classification in audio. The findings indicate the substantial promise that could be offered by artificial intelligence in real-time sentiment analysis and corresponding applications to diverse areas, including mental healthcare, customer service, and human-computer interaction.