Description: Hybrid Multimodal Systems are technological approaches that integrate multiple data modalities, such as text, audio, images, and video, using various techniques to enhance performance in specific tasks. These systems can process and analyze information from different sources simultaneously, allowing them to provide more accurate and comprehensive results. The combination of modalities enables the system to leverage the strengths of each data type, facilitating a richer and more contextualized understanding of the information. For instance, in the field of artificial intelligence, a multimodal system can combine audio data with visual information, such as lip movements, to improve recognition accuracy. Furthermore, these systems often incorporate machine learning and natural language processing techniques, allowing them to adapt and learn from new data over time. The relevance of Hybrid Multimodal Systems lies in their ability to tackle complex problems that require a comprehensive understanding of multiple types of information, making them valuable tools in various fields such as robotics, healthcare, and education.
