It is a proven fact that NLU systems are capable of detecting emotions in text. Recent research demonstrates that machine learning approaches, particularly those utilising neural networks, are highly effective at identifying a range of emotions from textual data, including joy, sadness, anger, fear, love and surprise. The models have demonstrated high accuracy rates in emotion detection tasks, thereby enhancing human-machine interactions. This is achieved by enabling systems to recognise and respond to users’ emotional states during communication.
