Eric R. Buhrke

Applying telepresence to incident management: The virtual incident command center

This paper describes an application of telepresence technology to the incident management domain. The system combines national guidelines for incident management with many aspects of collaborative virtual environments to enable effective communication between first responders in the field and remotely located command personnel. A brief overview of existing incident management systems is given, followed by a set of requirements for future systems. We then describe our virtual incident command center (VICC) prototype, explain how it addresses the requirements, and outline our future plans. Finally, we report feedback from ongoing demonstrations of the prototype system that supports our contention that VICC represents a unique solution to the incident management problem.

A generalization of the maximum a posteriori training algorithm for mixture priors

Prior information about the operating environment of a speech recognizer is often general and abstract. Frequently information such as the number of speakers with foreign accents or the number of callers using cellular phones is readily available. Incorporating this information during model training is difficult. This paper generalizes the popular MAP training algorithm derived by Gauvain and Lee (1994) so that more prior information can be utilized during training. The priors are in the form of mixture distributions with each mixture component representing a unique property of the data and the mixing weights defined by the a priori constraints. Using the training algorithms derived here it is shown that significant performance improvements can be obtained.