Published Paper Details:

Speech and emotion recognition over fusion of visual and vocal expression using artificial intelligence is a rapidly evolving field of research that aims to develop intelligent systems capable of accurately interpreting human emotions based on a combination of audio and visual cues. In this approach, computer vision, speech processing, and machine learning techniques are combined to analyze human behavior and emotions. This paper provides an overview of the techniques and challenges involved in speech and emotion recognition over fusion of visual and vocal expression using artificial intelligence. It also highlights some of the potential applications of these systems in healthcare, education, and customer service. Despite recent advancements in the field, there are still challenges to be addressed, such as the variability of emotions across different individuals and cultures, and the lack of standardization in emotion labeling. Overall, the potential benefits of these systems are vast, and with continued research and development, they have the potential to significantly improve our understanding of human emotions and behavior. In the field of artificial intelligence and machine learning, speech recognition and emotion recognition are two exciting issues. Speech recognition refers to a computer's ability to understand and transcribe spoken language, whereas emotion recognition refers to a computer's ability to recognise and classify the emotions expressed by a person through their speech.