Utilizing AI and Machine Learning for Human Emotional Analysis through Speech-to-Text Engine Data Conversion

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) technologies have revolutionized various domains, and one of their fascinating applications is in analyzing human emotions through speech-to-text data conversion. This article delves into the innovative use of AI and ML to process spoken words into text and subsequently evaluate human emotions embedded within the speech. We explore the development of speech-to-text technologies, the essential function of natural language processing (NLP), and the use of deep learning models to understand emotional cues. Our research discoveries illustrate how these technologies are altering fields like mental health, customer service, and market research, granting deeper understanding of human emotional states. By scrutinizing emotions conveyed in spoken language, artificial intelligence (AI) and machine learning (ML).