The development of voice technology has reached a critical juncture where understanding the emotional nuances behind human speech is becoming increasingly important. Current voice assistants often struggle to recognize emotions, which can lead to misinterpretation and a breakdown in dialogue. Emotion recognition is essential for creating an empathetic and affective conversation between humans and machines. Research is being conducted by companies such as Speechmatics to improve emotion recognition accuracy, including the use of self-supervised learning and exploring diverse data sets like TV broadcasts and phone calls with less human-labeled data. By analyzing real-world scenarios with varying levels of noise and emotions, these studies aim to better understand how emotions impact speech-to-text technology and develop more accurate and inclusive systems.