End-to-End Automatic Speech Recognition (ASR) systems streamline the process of converting spoken language into text by using a single neural network model, eliminating the need for separate components like acoustic, language, and pronunciation models. This approach simplifies training and optimization, often resulting in improved performance and adaptability across different languages and dialects compared to traditional ASR systems.