A dynamic content summarization system for opportunistic driver infotainment

The in-vehicle experience offers a unique challenge for delivering the right amount of information to the driver at the right time. The level of attention required to successfully manage the driving task is often in variable. An ideal in vehicle information delivery system would deliver content to the driver only during low task demand times, such as waiting at a stop light, when the driver's safety would be minimally compromised. The system would also have to respond to sudden changes in the situation such as driver interruption or distraction and terminate gracefully, allowing the driver to refocus on the driving task. In this paper, we present an embedded natural language processing (NLP) system that delivers speech synthesized summarized text content into tailored time slices. The system is also designed to respond dynamically to interruptions. We anticipate that this system could safely deliver speech synthesized content to drivers and allow them to make the most of their time on the road. We have implemented this system on an Atom Z530 processor with 1GB of RAM, a processor comparable to those found in factory installed In-Vehicle Infotainment (IVI) systems and have evaluated it in a laboratory test using a standard NLP corpus to demonstrate this potential.