Tools for building asynchronous servers to support speech and audio applications
UIST '92 Proceedings of the 5th annual ACM symposium on User interface software and technology
Voice communication with computers: conversational systems
Voice communication with computers: conversational systems
Play it again: a study of the factors underlying speech browsing behavior
CHI 98 Cconference Summary on Human Factors in Computing Systems
Introduction to the special issue on summarization
Computational Linguistics - Summarization
Reading on-the-go: a comparison of audio and hand-held displays
Proceedings of the 8th conference on Human-computer interaction with mobile devices and services
Plastic: a metaphor for integrated technologies
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
Enabling micro-entertainment in vehicles based on context information
Proceedings of the 2nd International Conference on Automotive User Interfaces and Interactive Vehicular Applications
Synthetic speech for real time direction-giving
IEEE Transactions on Consumer Electronics
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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.